Dissertations / Theses: 'Social-based'

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Rangiha, M. E. "A framework for social BPM based on social tagging." Thesis, City University London, 2016. http://openaccess.city.ac.uk/14999/.

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Traditional Business Process Management (BPM) has a number of limitations. The first one is the typical separation between process design and execution, which often causes discrepancies between the processes as they are designed and the way in which they are actually executed. Additionally, because of this separation, valuable first-hand knowledge generated during process execution may remain unused during process design and also prevented to be shared within the organisation. Social BPM, which predicates to integrate social software into the BPM lifecycle, has emerged as an answer to such limitations. Although there have been a number of approaches to Social BPM, they have not been able to address all the issues of traditional BPM. This thesis proposes a novel Social BPM framework in which social tagging is used to capture process knowledge emerging during the enactment and design of the processes. Process knowledge concerns both the type of activities chosen to fulfil a certain goal (i.e. what needs doing), and the skills and experience of users in executing specific tasks (i.e. skills which are needed to do it). Such knowledge is exploited by recommendation tools to support the design and enactment of future process instances. This framework overcomes the limitations of traditional BPM systems as it removes the barrier between the design and execution of the processes and also enables all users to be part of the different phases of the BPM lifecycle. We first provide an analysis of the literature to position our research area, and then we provide an overview of our framework discussing its specification and introducing a static conceptual model of its main entities. This framework is then elaborated further with a more dynamic model of the behaviour and, in particular, of the role and task recommendations, which are supported by social tagging. These mechanisms are then applied in a running example. Finally the framework is evaluated through the implementation of a prototype and its application in a case study. The thesis ends with a discussion about the different evaluation approaches of the proposed framework, limitations of our framework and future research.

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Eliasson, Benitha. "Social Work Approaching Evidence-Based Practice. : Rethinking Social Work." Doctoral thesis, Luleå tekniska universitet, Arbetsvetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-18343.

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The Swedish public sector has undergone major changes over the last decades, with increased demands to be effective and perform their tasks with high quality, but also with the demand to increase the influence of users and citizens over the support given. This development has influenced how social services organise and how their work is perform, and is one motive given as to why evidence-based practice was introduced. This development can also be traced back to the manager philosophy new public management and neo-liberalism. Evidence-based practice has its origin in evidence-based medicine, which had a large impact internationally from the 1990s.Although there are different opinions concerning how evidence-based practiceshould be understood is often described on the basis of Sackett et al.’s (2000) definition which regards evidence-based practice as an integration of different knowledge sources – the best evidence, clinical or professional expertise and the values and preferences of users. The professional have the responsibility to use all these knowledge sources in the daily work.The purpose of this thesis is to describe and analyse different processes of the introduction of evidence-based practice. One aspect is what these processes have contributed to in terms of organising ways of working and management within social services; another aspect concerns what this means for social work. With a combination of new institutional organisational theory and Berger and Luckmann’s (1967) insights into the social construction of everyday life, it is possible to analyse the introduction of evidence-based practice as a process, moving between a macro, meso and micro perspective. The empirical base for this thesis is interviews with 33 personnel from different professions and organisations. Those interviewed from thesocial services include social workers within individual and family services and socialservices managers, as well as regional representatives from a Research and Development Unit. To understand the development of evidence-based practice and its proliferation into social services I also interviewed doctors from health care in a County Council.New institutional organisational theory is useful for understanding how differentways of organising activities are spread between and within organisations. With concepts used in new institutional theory, the focus is on how evidence-based practice travels from medicine to social work, and from a national level to the local social services level, via the regional level. Giddens (1990) terms ‘disemedding’ and ‘reembedding’ are used. Different isomorphic processes are recognised in these processes, as well as strategies to decouple or loosely couple evidence-based practice from social services ordinary activities as a way to gain legitimacy. The main findings in the thesis are that evidence-based practice has been introduced with evidence-based medicine as a role model, and that this has been done from different conditions. As is described in the interviews, the development of evidencebased practice has been controlled from national organisations such as the government, the National Board of Health and Welfare and in recent years also the Swedish Association of Local Authorities and Region, while the development within the medical area was governed by national organisations but performed by the medical profession, which advocated the introduction of evidence-based practice within the profession. The regional representatives largely support the myth that is presented of evidence-based practice, and have a central responsibility in the national initiativesconducted; they are intermediary between the national initiatives on development work and the local practice. When evidence-based practice is introduced in social work this has entailed loosely coupling between the myth about evidence-based practice and the ordinary activities, this strategy is especially obvious among social services managers. Furthermore, when a medical model of evidence-based practice is used, although with a broader approach, the introduction of evidence-based practice does not reflect the social workers’ education, profession and ways of working in the same way as evidence-based medicine reflects the doctors’ education, profession andway of working. The intention to analyse the introduction of evidence-based practice from a micro perspective is about understanding how evidence-based practice is received by the social worker and their managers. When the interviews with the doctors, social workers and managers are analysed there is less coherence between evidence-based practice and social workers’ work than between evidence-based medicine and doctors’ work. This means that social workers have to shape and construct their daily work anew through internalising the new habits and routines into everyday work, something that takes energy and time, which most interviewees feel does not exist.This thesis also highlights the need for social work to approach evidence-based practice both at an organisational and a structural level, and from the level where the daily work is performed by social workers. Finally, there exists among almost all interviewees a great interest in introducing evidence-based practice, especially among the social workers, but at the moment it is not re-embedded in social work.

Godkänd; 2014; 20140731 (beneli); Nedanstående person kommer att disputera för avläggande av filosofie doktorsexamen. Namn: Benitha Eliasson Ämne: Arbetsvetenskap/Human Work Science Avhandling: Social Work Approaching Evidence-Based Practice Rethinking Social Work Opponent: Professor of Health Care Organisation Mike Dent, Faculty of Health Sciences, Staffordshire University, Storbritannien Ordförande: Professor Elisabeth Berg, Avd för arbetsvetenskap, Institutionen för ekonomi, teknik och samhälle, Luleå tekniska universitet Tid: Måndag den 29 september 2014, kl 13.00 Plats: A109, Luleå tekniska universitet

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Tang, Hon Cheong 1980. "Gravity-based trust model for web-based social networks." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=112366.

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Web-based social networks have become one of the most popular applications on the Internet in recent years. However, most of the social networks rely on some simplistic trust models to manage trust information of the users, which can cause problems ranging from unsatisfied user experience to exposure to malicious users. This thesis proposes a gravity-based trust model to enhance the aggregation of personal trust information into a subjective reputation system. This new model maps all users on the social network into n-dimensional Euclidean spaces based on their direct trust information, and creates a trust social neighborhood for each user. The reputation of a target user is determined by applying gravity model to the information from both target's and observer's trust social neighborhood. A prototype of this trust model is implemented in order to evaluate the effects of varying different parameters of the gravity-based trust model.

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Erlandsson, Fredrik. "On social interaction metrics : social network crawling based on interestingness." Licentiate thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00596.

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With the high use of online social networks we are entering the era of big data. With limited resources it is important to evaluate and prioritize interesting data. This thesis addresses the following aspects of social network analysis: efficient data collection, social interaction evaluation and user privacy concerns. It is possible to collect data from online social networks via their open APIs. However, a systematic and efficient collection of online social networks data is still challenging. To improve the quality of the data collection process, prioritizing methods are statistically evaluated. Results suggest that the collection time can be reduced by up to 48% by prioritizing the collection of posts. Evaluation of social interactions also require data that covers all the interactions in a given domain. This has previously been hard to do, but the proposed crawler is capable of extracting all social interactions from a given page. With the extracted data it is for instance possible to illustrate indirect interactions between different users that do not necessarily have to be connected. Methods using the same data to identify and cluster different opinions in online communities have been developed. These methods are evaluated with the too Linguistic Inquiry and Word Count. The privacy of the content produced; and the users’ private information provided on social networks is important to protect. Users must be aware of the consequence of posting in online social networks in terms of privacy. Methods to protect user privacy are presented. The proposed crawler in this thesis has, over the period of 20 months, collected over 38 million posts from public pages on Facebook covering: 4 billion likes and 340 million comments from over 280 million users. The performed data collection yielded one of the largest research dataset of social interactions on Facebook today, enabling qualitative research in form of social network analysis.

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Ariyattu, Resmi. "Towards federated social infrastructures for plug-based decentralized social networks." Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1S031/document.

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Dans cette thèse, nous abordons deux problèmes soulevés par les systèmes distribués décentralisés - le placement de réseaux logiques de façon compatible avec le réseau physique sous-jacent et la construction de cohortes d'éditeurs pour dans les systèmes d'édition collaborative. Bien que les réseaux logiques (overlay networks) été largement étudiés, la plupart des systèmes existant ne prennent pas ou prennent mal en compte la topologie du réseau physique sous-jacent, alors que la performance de ces systèmes dépend dans une grande mesure de la manière dont leur topologie logique exploite la localité présente dans le réseau physique sur lequel ils s'exécutent. Pour résoudre ce problème, nous proposons dans cette thèse Fluidify, un mécanisme décentralisé pour le déploiement d'un réseau logique sur une infrastructure physique qui cherche à maximiser la localité du déploiement. Fluidify utilise une stratégie double qui exploite à la fois les liaisons logiques d'un réseau applicatif et la topologie physique de son réseau sous-jacent pour aligner progressivement l'une avec l'autre. Le protocole résultant est générique, efficace, évolutif et peut améliorer considérablement les performances de l'ensemble. La deuxième question que nous abordons traite des plates-formes d'édition collaborative. Ces plates-formes permettent à plusieurs utilisateurs distants de contribuer simultanément au même document. Seuls un nombre limité d'utilisateurs simultanés peuvent être pris en charge par les éditeurs actuellement déployés. Un certain nombre de solutions pair-à-pair ont donc été proposées pour supprimer cette limitation et permettre à un grand nombre d'utilisateurs de collaborer sur un même document sans aucune coordination centrale. Ces plates-formes supposent cependant que tous les utilisateurs d'un système éditent le même jeu de document, ce qui est peu vraisemblable. Pour ouvrir la voie à des systèmes plus flexibles, nous présentons, Filament, un protocole décentralisé de construction de cohorte adapté aux besoins des grands éditeurs collaboratifs. Filament élimine la nécessité de toute table de hachage distribuée (DHT) intermédiaire et permet aux utilisateurs travaillant sur le même document de se retrouver d'une manière rapide, efficace et robuste en générant un champ de routage adaptatif autour d'eux-mêmes. L'architecture de Filament repose sur un ensemble de réseaux logiques auto-organisées qui exploitent les similarités entre jeux de documents édités par les utilisateurs. Le protocole résultant est efficace, évolutif et fournit des propriétés bénéfiques d'équilibrage de charge sur les pairs impliqués
In this thesis, we address two issues in the area of decentralized distributed systems: network-aware overlays and collaborative editing. Even though network overlays have been extensively studied, most solutions either ignores the underlying physical network topology, or uses mechanisms that are specific to a given platform or applications. This is problematic, as the performance of an overlay network strongly depends on the way its logical topology exploits the underlying physical network. To address this problem, we propose Fluidify, a decentralized mechanism for deploying an overlay network on top of a physical infrastructure while maximizing network locality. Fluidify uses a dual strategy that exploits both the logical links of an overlay and the physical topology of its underlying network to progressively align one with the other. The resulting protocol is generic, efficient, scalable and can substantially improve network overheads and latency in overlay based systems. The second issue that we address focuses on collaborative editing platforms. Distributed collaborative editors allow several remote users to contribute concurrently to the same document. Only a limited number of concurrent users can be supported by the currently deployed editors. A number of peer-to-peer solutions have therefore been proposed to remove this limitation and allow a large number of users to work collaboratively. These decentralized solution assume however that all users are editing the same set of documents, which is unlikely to be the case. To open the path towards more flexible decentralized collaborative editors, we present Filament, a decentralized cohort-construction protocol adapted to the needs of large-scale collaborative editors. Filament eliminates the need for any intermediate DHT, and allows nodes editing the same document to find each other in a rapid, efficient and robust manner by generating an adaptive routing field around themselves. Filament's architecture hinges around a set of collaborating self-organizing overlays that utilizes the semantic relations between peers. The resulting protocol is efficient, scalable and provides beneficial load-balancing properties over the involved peers

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Sairin, Sjafri. "Javanese trah : kin-based social organization /." Yogyakarta : Gadjah Mada university press, 1992. http://catalogue.bnf.fr/ark:/12148/cb374310288.

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Th. M.A.--Social anthropology--Canberra--Australian national university, 1980. Titre de soutenance : Thèse soutenue sous le titre : "Javanese trah : a preliminary description of a type of Javanese social organization.
Bibliogr. p. 92-96.

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Chambers, Cynthia R. "Creating Meaningful, Community-Based Social Networks." Digital Commons @ East Tennessee State University, 2014. https://dc.etsu.edu/etsu-works/3851.

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BAFFA, AUGUSTO CESAR ESPINDOLA. "STORYTELLING BASED ON AUDIENCE SOCIAL INTERACTION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2015. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=25300@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
Ao contar uma história, o narrador usa toda sua habilidade para entreter a audiência. Esta tarefa não define apenas o ato de contar uma história, mas também a capacidade de compreender as reações do público durante a narração da história. Não é muito difícil adaptar uma história para um único individuo baseando-se em suas preferências e escolhas anteriores, porém, a tarefa de escolher o que é melhor para um grupo torna-se bastante complicada. A seleção por votação de uma maioria pode não ser eficiente pois descarta alternativas que foram consideradas secundárias por alguns indivíduos, mas que funcionariam melhor para o grupo em questão. Desta forma, a seleção descuidada dos eventos em uma história poderia causar a ruptura do grupo, fazendo com que algumas pessoas desistam de continuar assistindo pois não foram agradadas. Esta tese propõe uma metodologia para criar histórias adaptadas para a audiência com base em traços de personalidade e preferências de cada indivíduo. Como uma audiência pode ser composta de indivíduos com preferências semelhantes ou mistas, é necessário considerar uma solução de meio-termo com base nas opções individuais. Além disso, os indivíduos podem ter algum tipo de relação com os outros que influenciam suas decisões. O modelo proposto aborda todas as etapas da missão de agradar ao público. Deve inferir quais são as preferências, calcular a recompensa das cenas para todos os indivíduos, estimar as escolhas de forma independente e em grupo, e permitir sistemas de Storytelling Interativos encontrar a história que maximiza a recompensa esperada da audiência. O modelo proposto pode ser facilmente estendido a outras áreas que envolvem usuários interagindo com ambientes digitais.
To tell a story, the storyteller uses all his/her skills to entertain an audience. This task not only relies on the act of telling a story, but also on the ability to understand reactions of the audience during the telling of the story. It is not so difficult to adapt a story for a single individual based on his/her preferences and previous choices. However, the task of choosing what is best for a group becomes quite complicated. The selection by majority voting cannot be effective because it can discard alternatives that are secondary for some individuals, but that would work better for the group in question. Thus, the careless selection of events in a story could cause audience splitting, causing some people to give up keep watching because they were not pleased. This thesis proposes a new methodology to create tailored stories for an audience based on personality traits and preferences of each individual. As an audience may be composed of individuals with similar or mixed preferences, it is necessary to consider a middle ground solution based on the individual options. In addition, individuals may have some kind of relationship with others who influence their decisions. The proposed model addresses all steps in the quest to please the audience. It infers what the preferences are, computes the scenes reward for all individuals, estimates their choices independently and in group, and allows Interactive Storytelling systems to find the story that maximizes the expected audience reward. The proposed model can easily be extended to other areas that involve users interacting with digital environments.

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Carslaw, Gregory. "Agent based modelling in social psychology." Thesis, University of Birmingham, 2013. http://etheses.bham.ac.uk//id/eprint/4068/.

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Agent based modelling is a tool that has been successful in developing theories in a wide range of fields, but its application to social psychology is still in its infancy. This body of work applies the agent based modelling method to areas of social psychology including contact theory, group dynamics, altruistic behaviour and social identity theory. In each of these areas an agent based model is introduced that furthers the relevant theories and taken together these models demonstrate the effectiveness of some of the techniques outlined in existing research as well as producing a unique recommendation for the applications of agent based modelling in social psychology. In the fourth and fifth chapters three existing agent based models are extended in line with multiple identity theory and doing so produces novel results that improve upon the explanations of the original models. Therefore it is concluded that for agent based modelling in social psychology it is important to always consider the impact of multiple identities upon our modelling efforts rather than always simulating the minimum group identities necessary to test a hypothesis.

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Chatzilari, Elisavet. "Social media based scalable concept detection." Thesis, University of Surrey, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.658829.

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Although over the past decades there has been remarkable progress in the field of computer vision, scientists are still confronted with the problem of designing techniques and frameworks that can easily scale to many different domains and disciplines. It is true that state of the art approaches cannot produce highly effective models, unless there is dedicated, and thus costly, human supervision in the process of learning. Recently, we have been witnessing the rapid growth of social media (e.g. images, videos, etc.) that emerged as the result of users' willingness to communicate, socialize, collaborate and share content. The outcome of this massive activity was the generation of a tremendous volume of user contributed data available on the Web, usually along with an indication of their meaning (i.e. tags). This has motivated researchers to investigate whether the Collective Intelligence that emerges from the users' contributions inside a Web 2.0 application, can be used to remove or ease the burden for dedicated human supervision. By doing so, this social content can facilitate scalable but also effective learning. In this thesis we contribute towards this goal by tackling scalability in two ways; first, we opt to gather effortlessly high quality training content in order to facilitate scalable learning to numerous concepts, which will be referred to as system scalability. Towards this goal, we examine the potential of exploiting user tagged images for concept detection under both unsupervised and semi-supervised frameworks. Second, we examine the scalability issue from the perspective of computational complexity, which we will refer to as computational scalability. In this direction, we opt to minimize the computational cost while at the same time minimize the inevitable performance loss by predicting the most prominent concepts to process further.

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Leung, Kwan Wai. "Commentary-based social media clustering with concept and social network discovery." HKBU Institutional Repository, 2011. https://repository.hkbu.edu.hk/etd_ra/1303.

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Lai, Ka Chon. "Constructing social networks based on image analysis." Thesis, University of Macau, 2012. http://umaclib3.umac.mo/record=b2586279.

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Lamborn, Peter C. "January : search based On social insect behavior /." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd801.pdf.

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Stewart, Denyse. "Social change and community-based literacy programs." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape11/PQDD_0007/MQ40676.pdf.

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Brown, Holly Beth. "Social Justice and Community-Based Art Education." Thesis, The University of Arizona, 2010. http://hdl.handle.net/10150/193320.

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Both in and out of the classroom, critically discussing and exploring the issues of gender, race, power, equality, and social justice can be a social and emotional minefield for educators and students alike. In politically charged times, escaping pre-formulated reactions and creating real change and empathy can seem a nearly impossible task. Some educators have turned to the visual and creative arts to provide students with emotional connectedness, visceral responses, and modes of self-expression. In this study, I examine two education programs to understand the effectiveness of social justice pedagogical methods using phenomenological research. My focus is on the educators' experiences, influences, and personal pedagogies. I plan to highlight three successful programs to better understand how complex and emotional issues can be better explored through art and visual culture and how other educators can adapt these methods to their own classrooms.

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Fan, Xiaoguang, and 樊晓光. "Study of social-network-based information propagation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B50899600.

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Information propagation has attracted increasing attention from sociologists, marketing researchers and Information Technology entrepreneurs. With the rapid developments in online and mobile social applications like Facebook, Twitter, and LinkedIn, large-scale, high-speed and instantaneous information dissemination becomes possible, spawning tremendous opportunities for electronic commerce. It is non-trivial to make an accurate analysis on how information is propagated due to the uncertainty of human behavior and the complexity of the social environment. This dissertation is concerned with exploring models, formulations, and heuristics for the social-network-based information propagation process. It consists of three major parts: information diffusion through online social network, modeling social influence propagation, and social-network-based information spreading in opportunistic mobile networks. Firstly, I consider the problem of maximizing the influence propagation through online social networks. To solve it, I introduce a probabilistic maximum coverage problem, and propose a cluster-based heuristic and a neighbor-removal heuristic for two basic diffusion models, namely, the Linear Threshold Model and the Independent Cascade Model, respectively. Realizing that the selection of influential nodes is mainly based on the accuracy and efficiency in estimating the social influence, I build a framework of up-to-2-hop hierarchical network to approximate the spreading of social influence, and further propose a hierarchy-based algorithm to solve the influence maximization problem. Our heuristic is proved to be efficient and robust with competitive performance, low computation cost, and high scalability. The second part explores the modeling on social influence propagation. I develop an analytical model for the influence propagation process based on discrete-time Markov chains, and deduce a close-form equation to express the n-step transition probability matrix. We show that given any initial state the probability distribution of the converged network state could be easily obtained by calculating a matrix product. Finally, I study the social-network-based information spreading in opportunistic mobile networks by analyzing the opportunistic routing process. I propose three social-network-based communication pattern models and utilize them to evaluate the performance of different social-network-based routing protocols based on several human mobility traces. Moreover, I discuss the fairness evaluation in opportunistic routing, and propose a fair packet forwarding strategy which operates as a plugin for traditional social- network-based routing protocols. My strategy improves the imbalance of success rates among users while maintaining approximately the same system throughput.
published_or_final_version
Electrical and Electronic Engineering
Doctoral
Doctor of Philosophy

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Khelghatdoust, Mansour. "Gossip based peer sampling in social overlays." Thesis, KTH, Kommunikationsnät, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-144278.

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Performance of many P2P systems depends on the ability to construct a ran- dom overlay network among the nodes. Current state-of-the-art techniques for constructing random overlays have an implicit requirement that any two nodes in the system should always be able to communicate and establish a link be- tween them. However, this is not the case in some of the environments where distributed systems are required to be deployed, e.g, Decentralized Online So- cial Networks, Wireless networks, or networks with limited connectivity because of NATs/firewalls, etc. In such restricted networks, every node is able to com- municate with only a predefined set of nodes and thus, the existing solutions for constructing random overlays are not applicable.In this thesis we propose a gossip based peer sampling service capable of running on top of such restricted networks and producing an on-the-fly random overlay. The service provides ev- ery participating node with a set of uniform random nodes from the network, as well as efficient routing paths for reaching those nodes via the restricted net- work. We perform extensive experiments on four real-world networks and show that the resulting overlays rapidly converge to random overlays. The results also exhibit that the constructed random overlays have self healing behaviour under churn and catastrophic failures.

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Wang, Guan. "Graph-Based Approach on Social Data Mining." Thesis, University of Illinois at Chicago, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3668648.

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Powered by big data infrastructures, social network platforms are gathering data on many aspects of our daily lives. The online social world is reflecting our physical world in an increasingly detailed way by collecting people's individual biographies and their various of relationships with other people. Although massive amount of social data has been gathered, an urgent challenge remain unsolved, which is to discover meaningful knowledge that can empower the social platforms to really understand their users from different perspectives.

Motivated by this trend, my research addresses the reasoning and mathematical modeling behind interesting phenomena on social networks. Proposing graph based data mining framework regarding to heterogeneous data sources is the major goal of my research. The algorithms, by design, utilize graph structure with heterogeneous link and node features to creatively represent social networks' basic structures and phenomena on top of them.

The graph based heterogeneous mining methodology is proved to be effective on a series of knowledge discovery topics, including network structure and macro social pattern mining such as magnet community detection (87), social influence propagation and social similarity mining (85), and spam detection (86). The future work is to consider dynamic relation on social data mining and how graph based approaches adapt from the new situations.

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Laraqui, Jawad. "Activity based interfaces in online social networks." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/41658.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
Includes bibliographical references (p. 51).
The goal of the project is to explore how activity-based interfaces can create more meaningful experiences for the users and builders of online social networking sites. Medina, a social-networking site based on the idea of exchanging knowledge, explores new interfaces for visualizing connections between people and ideas. The site constantly measures interactions between people and their interests in order to create a more accurate picture of what relationships and information are important.
by Jawad Laraqui.
M.Eng.

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Karunatillake, Nishan C. "Argumentation-based negotiation in a social context." Thesis, University of Southampton, 2006. https://eprints.soton.ac.uk/263130/.

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Argumentation-based negotiation (ABN) is gaining increasing importance as a fundamental method of interaction in multi-agent systems. In essence, ABN enhances the ways agents can interact within a negotiation encounter. In particular, it allows agents to justify their demands, criticise each others’ proposals, and add comments to their statements during a negotiation encounter. Furthermore, ABN gives them the capability to exchange explicit arguments, such as promises, threats, appeals, and other forms of persuasive locutions, to influence one another during a negotiation dialogue. Such enhancements lead to richer forms of negotiation than have hitherto been possible in game-theoretic or heuristic-based models. Therefore, many argue that endowing the agents with the ability to argue during their negotiation interactions, not only facilitates more realistic rational dialogues, but also allows an effective means of resolving different forms of conflicts endemic to multi-agent societies. Even though ABN is argued to be an effective means of resolving conflicts, its operation within multi-agent systems incurs certain computational overheads. In particular, it takes time for an agent to argue and convince an opponent to change its demands and yield to a less favourable agreement within an ABN encounter. It also takes computational effort for both parties of the conflict to carry out the necessary reasoning required to generate, select, and evaluate an appropriate and a convincing set of arguments required for such an encounter. On the other hand, within a multi-agent society, not all conflicts need to be resolved. In some instances conflicts can be avoided by other nonarguing means. For instance, in certain situations agents may be able to avoid conflicts by finding an alternative resource to achieve their actions instead of arguing over a conflicting one. They also may be able to re-plan to achieve the same objective through a different means and, thereby, remove the conflict without argument. In the presence of such overheads and given the alternatives available, this thesis argues that computationally bounded entities such as agents need to consider two critical questions before they use ABN to manage their conflicts. First is when to argue; that is, under what conditions would ABN, as opposed to other non-arguing methods, present a better option for agents to overcome conflicts. Second is how to argue; that is, a computationally tractable method and a set of strategies to successfully formulate such sophisticated ABN dialogues. To this end, this thesis forwards a detailed theoretical and empirical study to address both these research questions. In more detail, first we formulate a novel ABN framework that allows agents to argue, negotiate and, thereby, resolve conflicts in structured multi-agent systems. The framework is unique in the way that it explicitly captures social influences endemic to such agent societies and, in turn, allows agents to use them constructively in their ABN dialogues. Having formulated the framework, we then map it into the computational context of a multi-agent task allocation scenario. In so doing, we bridge the gap between theory and practice and provide a test-bed to evaluate how our ABN model can be used to manage and resolve conflicts in multi-agent societies. Our experimental analysis on when to argue shows a clear inverse correlation between the benefit of arguing and the resources available within the context. It also shows that arguing selectively is both a more efficient and a more effective strategy than doing so in an exhaustive manner. Furthermore, we show that when agents operate under imperfect knowledge conditions, an arguing approach allows them to perform more effectively than a non-arguing one. On the issue of how to argue, we show that arguing earlier in an ABN interaction presents a more efficient method than arguing later in the interaction. Moreover, during an ABN interaction, allowing agents to negotiate their social influences presents both an effective and an efficient method which will enhance their performance within a society.

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Saleem, Muhammad. "Location Analytics for Location-Based Social Networks." Doctoral thesis, Universite Libre de Bruxelles, 2018. https://dipot.ulb.ac.be/dspace/bitstream/2013/271131/5/contratMS.pdf.

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The popularity of location empowered devices such as GPS enabled smart-phones has immensely amplified the use of location-based services in social networks. This happened by allowing users to share Geo-tagged contents such as current locations/check-ins with their social network friends. These location-aware social networks are called Location-based Social Networks (LBSN), and examples include Foursquare and Gowalla. The data of LBSNs are being used for providing different kinds of services such as the recommendation of locations, friends, activities, and media contents, and the prediction of user's locations. To provide such services, different queries are utilized that exploit activity/check-in data of users. Usually, LBSN data is divided into two parts, a social graph that encapsulates the friendships of users and an activity graph that maintains the visit history of users at locations. Such a data separation is scalable enough for processing queries that directly utilize friendship information and visit history of users. These queries are called user and activity analytic queries. The visits of users at locations create relationships between those locations. Such relationships can be built on different features such as common visitors, geographical distance, and mutual location categories between them. The process of analysing such relationships for optimizing location-based services is termed Location Analytics. In location analytics, we expose the subjective nature of locations that can further be used for applications in the domain of prediction of visitors, traffic management, route planning, and targeted marketing.In this thesis, we provide a general LBSN data model which can support storage and processing of queries required for different applications, called location analytics queries. The LBSN data model we introduce, segregates the LBSN data into three graphs: the social graph, the activity graph, and the location graph. The location graph maintains the interactions of locations among each other. We define primitive queries for each of these graphs. In order to process an advanced query, we express it as a combination of these primitive queries and process them on corresponding graphs in parallel. We further provide a distributed data processing framework called GeoSocial-GraphX (GSG). GSG implements the aforementioned LBSN data model for efficient and scalable processing of the queries. We further exploit the location graph for providing novel location analytics queries in the domain of influence maximization and visitor prediction. We introduce a notion of location influence. Such influence can capture the interactions of locations based on their visitors and can be used for propagation of information between them. The applications of such a query lie in the domain of outdoor marketing, and simulation of virus and news propagation. We also provide a unified system IMaxer that can evaluate and compare different information propagation mechanisms. We further exploit the subjective nature of locations by analysing the mobility behaviour of their visitors. We use such information to predict the individual visitors as well as the groups of visitors (cohorts) in future for those locations. The prediction of visitors can be used for better event planning, traffic management, targeted marketing, and ride-sharing services.In order to evaluate the proposed frameworks and approaches, we utilize data from four real-life LBSNs: Foursquare, Brightkite, Gowalla, and Wee Places. The detailed LBSN data mining and statistically significant experimental evaluation results show the effectiveness, efficiency, and scalability of our proposed methods. Our proposed approaches can be employed in real systems for providing life-care services.
Doctorat en Sciences de l'ingénieur et technologie
The portal is not showing my complete name. The name (my complete name), I want to have on the diploma is "Muhammad Aamir Saleem". Please correct this issue.
info:eu-repo/semantics/nonPublished

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Bucci, Aleia. "Social entrepreneurs’ conceptions of incubator-based learning." Diss., University of Pretoria, 2020. http://hdl.handle.net/2263/79768.

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Research on entrepreneurial learning tends to focus on formal environments while entrepreneurs typically learn in non-formal environments such as business incubators. Despite this, incubators are rarely designed with learning in mind. Recent calls for the application of learning theories in incubation research along with a lack of prior studies on the subject led to informal learning theory as the lens to understand the qualitatively different ways in which social entrepreneurs experience learning within an incubator. The research was conducted in South Africa, characterised dichotomously by a relatively advanced economy with an immense social need. Through twenty phenomenographic interviews, eight conceptions of incubator-based learning were found: learnability, business concepts, entrepreneur concepts, practical application of knowledge, business transformation, personal transformation, having a champion, and co-created learning. Previous phenomenographic research has focused on formal learning environments but utilising the methodology in a non-formal learning environment led to two differences in commonly held conceptions of learning – no evidence of memorisation and two additional collective-focused conceptions. The eight conceptions were then used to create a model of the informal learning experience of social entrepreneurs within incubation programmes, contributing to the theory by demonstrating that this learning experience is different than informal learning experiences in other contexts. Further analysis showed the conceptions are experienced in five varying ways, characterised as learning by the archetypes of Maximiser, Transformer, Collaborator, Student, and Consumer. As a concept, learning archetypes are not new, but the creation and application of learning archetypes in the context of incubation programmes is novel. A phenomenographic outcome space mapped the characteristics of each archetype across each conception, visualising how different archetypes experience each conception, and therefore the overall experience of learning, in a distinct way. Incubators can utilise the findings to better support social entrepreneurs’ learning by providing content relevant to social entrepreneurs, focusing on participants’ identities as learners, and offering flexible and customisable programmes. Additionally, to create a more collaborative learning environment, incubators should consider relationship dynamics and learning potential when selecting participants.
Thesis (PhD)--University of Pretoria, 2020.
Gordon Institute of Business Science (GIBS)
DPhil
Unrestricted

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Baicu, Mihai-Catalin. "Social Sustainability in EU-Based Urban Regeneration." Thesis, Malmö universitet, Malmö högskola, Institutionen för Urbana Studier (US), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43203.

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The social dimension of sustainability has been underdefined and under researched when compared to the fields of economic and environmental sustainability. The paper explores the difficulty in understating the concept of social sustainability and the difficulty in operationalising the concept, items discussed in interviews. Through a qualitative content analysis, the paper highlights how the concept of social sustainability is positioned within the sustainability discourse and in a conflictual relationship with the economic and environmental sustainability. The concept of social sustainability is explored in the understanding of both a traditional and a new set of values, the latter being a weak instrument in operationalising compared to the former. The role of governance in navigating the interpretation of social sustainability is explored, with particular focus on policies as the result of decision-making process in governance. Partnerships structures are emphasised as an answer to incorporating social sustainability components of equity, empowerment, representation, and inclusion in policymaking. Urban regeneration is explored as an opportunity to change at local level, and EU policies are presented to highlight the discourse of urban regeneration to be more inclusive of social sustainability themes. Lastly, the case study of Leipzig East suggests the local authorities’ means to create a more socially sustainable governance structure during urban regeneration programmes. The case study shows strong local leadership and attention to power sharing during partnership schemes which involve public, private, and civic actors alike. The paper shows how Leipzig’s partnerships for urban regeneration fostered the creation of a more inclusive, democratic environment for both governance and residents alike.

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Hudson, Matthew. "Social presence in team-based digital games." Thesis, University of York, 2014. http://etheses.whiterose.ac.uk/9109/.

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This thesis explores the concept of social presence in team-based digital games, aiming to enlighten the core elements of social presence in this specific multi-user experience. The thesis achieves this exploration in three main ways, by using a novel approach to establish the core elements of social presence in team-based digital games, by developing a new measure for social presence specifically tailored for team-based digital games, and by exploring the effects of contextual gameplay factors on social presence in a large scale user study. The thesis documents the work carried out over the course of an Engineering Doctorate (EngD) sponsored by BAE Systems, who gave an industry perspective, helped to set the direction of the research and guide it throughout the program. The industry relevance to studying social presence in team-based digital games was the analogous nature of teambased games to virtual training technologies such as simulators and serious games, and the lack of understanding of social elements within these technologies. The research questions for this thesis were as follows: What is the nature of social presence in team-based digital games? How social presence is affected by sharing a team-based virtual environment with human or computer controlled entities? What other contextual elements encourage or reduce feelings of social presence? The first set of studies detailed in this thesis were a preliminary exploration of social presence in team-based digital games, a group of short user studies termed experiential vignettes, investigating the effect of agency on user experience. The experiential vignettes suggest that social presence is affected by a player’s perception of the other entities in the virtual environment, however the extent of the affect is highly dependent on task. These preliminary studies led to the development of a questionnaire designed to measure social presence in team-based digital games, the competitive and cooperative social presence questionnaire (CCPIG), developed and validated using user studies. The CCPIG was utilized and further validated in a large scale user study which aimed to explore the conceptual crossover between team trust and social presence, and how various contextual variables affected these concepts. This thesis shows that competitive and cooperative social presence are two distinct concepts, and that there is significant conceptual crossover between social presence and established notions of team trust. This thesis also shows that social presence is highly context dependent, affected by agency, familiarity with other players, team performance, and the nature of the game in which the experience occurs.

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Lloyd, Kirsten Ruth. "Social documents : the mediation of social relations in lens-based contemporary art." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/25934.

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This thesis examines the trajectory of the ‘social document’ in contemporary art since 1989. Though art’s turn towards documentary modes has now been widely noted, this study establishes a longer, more complex engagement with the dialogue between the lens and the situational immediacy of artists’ social interventions. I argue that the social documents that arise through the reconfigured artwork can be connected with the demand for the circulation of social knowledge and increasingly urgent questions of realism, a methodology that divided the avant-garde and neo-avant-garde of the 20th century. Central issues broached by the thesis include the demand for the extraction and re-articulation of truth, the role of visual representation in the address to totality and the emergence of (independent) knowledge and (critical) pedagogy as key sites of struggle. My analysis begins, in Part I, with a selective mapping of the historical terrain through which I offer re-readings of prescient works produced in the 1960s and 1970s in a range of capitalist and state socialist contexts including Mary Kelly, Grupo de Artistas de Vanguardia and Sanja Iveković. I then move on to a more detailed appraisal of the ascendancy of the social document in art following the collapse of the Berlin Wall and the consolidation of global capitalism, situating its various calibrations in relation to what I call biopolitical globalisation. Part II takes a thematic approach to the material, using case studies to examine a) the curatorial narrativisation and production of social documents, b) the relevance of feminist elaborations on theories of social reproduction to analyses of the social document and art history, c) the persistent invocation of ethics in discussions of works that document the social subjects of the new economy, d) the implications of addressing the social document as a realist enterprise. Artists discussed in Part II include Anton Vidokle, Martha Rosler, WochenKlausur, Dani Marti and Pilvi Takala.

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Berntsen, Gøran, and Bård Gamnes. "Social Entrepreneurship in 2011 : A framework for classifying ventures based on social efforts and social effects." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for industriell økonomi og teknologiledelse, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-15064.

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In this thesis we take the first steps towards developing a framework for evaluating the social efforts and effects of ventures, and investigate factors that may influence dynamics such a framework. Our work is divided into two papers.In the first paper (Thesis Paper A) we develop a conceptual framework for evaluating the social effort and social effect of ventures. The framework is theoretically based on literature reviews and in-depth, qualitative case studies. The purpose is to build a platform for qualitative analysis of ventures that lets us compare their social performance with their social intentions. The resulting framework is a two-by-two matrix, describing four classes of ventures. Factors influencing a venture’s movement from one class in the framework to another are examined. We find that changing the social effort of a venture does not immediately change its social effects. Finally, we suggest that understanding the dynamics of this framework is useful for both researchers, and managers wishing to reposition themselves.In the second paper (Thesis Paper B) we take the framework one step further by replacing the two-by-two matrix with two continuous dimensions. We then develop a quantitative method for evaluating ventures in the framework. In order to do so, we find a set of indicators to measure a venture’s social efforts and social effects. We apply this method to 19 ventures by conducting a survey. Our findings indicate a linear correlation between the social efforts and effects of the respondents, and that both ventures traditionally considered to be “social” and ventures considered to be “non-social” follow the same linearity. Surprisingly, we also find that none of our respondents score negatively on the social effects dimension. This leads us to question the sustainability of a venture with negative social effects as an important point for future research.Through both papers we see that an evaluation of the two dimensions “social efforts” and “social effects” provides a more accurate classification of ventures than a simple division of ventures into “social ventures” and “non-social ventures”. “Social Entrepreneurship in 2011”, the title of this thesis, is an increasingly important theme. It is important for both researchers and actors in this field to understand that any venture can have social properties. Questions of whether or not ventures are social may become superfluous. Instead, the focus should be on what effects ventures have on society and how they are performing compared to their social efforts. As society comes to expect more from all ventures, we believe that ventures, regardless of type, context, size, or industry, should be measured on the same dimensions.Our findings open for many interesting research possibilities, some of which are discussed in the papers. The applications of our work for venture managers are also discussed, and have to some degree been demonstrated already. In the second paper, we conducted a survey where we offered our respondents a report with their results. Several of the respondents said that the reports illustrated reality as they perceived it, and some found potential for improvement in areas they had not considered to be under their control. A sample report can be found after Thesis Paper B.

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Alahmadi, Dimah. "Recommender systems based on online social networks : an Implicit Social Trust And Sentiment analysis approach." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/recommender-systems-based-on-online-social-networks-an-implicit-social-trust-and-sentiment-analysis-approach(ac03f7e5-4fc0-4c4a-bace-82188823eb84).html.

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Recommender systems (RSs) provide personalised suggestions of information or products relevant to user's needs. RSs are considered as powerful tools that help users to find interesting items matching their own taste. Although RSs have made substantial progress in theory and algorithm development and have achieved many commercial successes, how to utilise the widely available information on Online Social Networks (OSNs) has largely been overlooked. Noticing this gap in existing research on RSs and taking into account a user's selection being greatly influenced by his/her trusted friends and their opinions, this thesis proposes a novel personalised Recommender System framework, so-called Implicit Social Trust and Sentiment (ISTS) based RSs. The main motivation was to overcome the overlooked use of OSNs in Recommender Systems and to utilise the widely available information from such networks. This work also designs solutions to a number of challenges inherent to the RSs domain, such as accuracy, cold-start, diversity and coverage. ISTS improves the existing recommendation approaches by exploring a new source of data from friends' short posts in microbloggings. In the case of new users who have no previous preferences, ISTS maps the suggested recommendations into numerical rating scales by applying the three main components. The first component is measuring the implicit trust between friends based on their intercommunication activities and behaviour. Owing to the need to adapt friends' opinions, the implicit social trust model is designed to include the trusted friends and give them the highest weight of contribution in recommendation encounter. The second component is inferring the sentiment rating to reflect the knowledge behind friends' short posts, so-called micro-reviews. The sentiment behind micro-reviews is extracted using Sentiment Analysis (SA) techniques. To achieve the best sentiment representation, our approach considers the special natural environment in OSNs brief posts. Two Sentiment Analysis methodologies are used: a bag of words method and a probabilistic method. The third ISTS component is identifying the impact degree of friends' sentiments and their level of trust by using machine learning algorithms. Two types of machine learning algorithms are used: classification models and regressions models. The classification models include Naive Bayes, Logistic Regression and Decision Trees. Among the three classification models, Decision Trees show the best Mean absolute error (MAE) at 0.836. Support Vector Regression performed the best among all models at 0.45 of MAE. This thesis also proposes an approach with further improvement over ISTS, namely Hybrid Implicit Social Trust and Sentiment (H-ISTS). The enhanced approach applies improvements by optimising trust parameters to identify the impact of the features (re-tweets and followings/followers list) on recommendation results. Unlike the ISTS which allocates equal weight to trust features, H-ISTS provides different weights to determine the different effects of the two trust features. As a result, we found that H-ISTS improved the MAE to be 0.42 which is based on Support Vector Regression. Further, it increases the number of trust features from two to five features in order to include the influence of these features in rating predictions. The integration of the new approach H-ISTS with a Collaborative Filtering recommender system, in particular memory-based, is investigated next. Therefore, existing users with a history of ratings can receive recommendations by fusing their own tastes and their friends' preferences using the two type of memory-based methods: user-based and item-based. H-ISTSitem is the integration of H-ISTS and item-based which provides the lowest error at 0.7091. The experiments show that diversity is better achieved using the H-ISTSuser which is the integration of H-ISTS and user-based technique. To evaluate the performance of these approaches, two real social datasets are collected from Twitter. To verify the proposed framework, the experiments are conducted and the results are compared against the most relevant baselines which confirmed that RSs have been successfully improved using OSNs. These enhancements demonstrate the effectiveness and promises of the proposed approach in RSs.

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Mthombeni, Sithembile. "Motivating factors of social entrepreneurs : the experiences of social entrepreneurs based in Gauteng." Diss., University of Pretoria, 2015. http://hdl.handle.net/2263/52265.

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Social entrepreneurs, by deploying simple but creative solutions to seemingly complex problems, are catalysts of transformational change. The innovations inherent in their initiatives have wide-ranging and beneficial impacts on society. These have particular application in the South African context, which is characterised by unemployment, poverty, HIV/AIDS, and lack of access to sufficient levels of healthcare and education. The innovations thus engendered are not only scalable and easy replicated, they also have relevance in the enhancing of mainstream commercial business models. Given that social entrepreneurs' activities commonly result in public utility, it is germane to understand the underlying motivations that inform their decision to engage with the field. The social entrepreneur approaches problems differently, he reframes what others see as challenges into opportunities to serve the unmet needs of the vulnerable in society. Thus it is useful to theorise about what motivates him to act. An exploratory, qualitative study was undertaken to gain insight into the inner workings of the psychological motivations driving these individuals to engage with social entrepreneurship. Semi-structured depth interviews were conducted with both social and commercial entrepreneurs, as well as with an expert in entrepreneurship. Through, context analysis utilising computer-aided software Atlas.ti The findings revealed a unique blend of motivations that inform individuals engagement with social entrepreneurship. Prosocial motivations, altruistic intentions and compassion, were found to be insufficient to induce individuals to engage with social entrepreneurship. The changemaker orientation as well as the desire to innovate and alignment to purpose were presented as core to the motivations of social entrepreneurs. Points of difference were established with commercial entrepreneurs. The study makes a useful contribution to the theory with regards to motivations underlying social entrepreneurial action. An understanding of these motivators not only informs the public sector, policymakers and practitioners, but also aids business s efforts to strengthen the field.
Mini Dissertation (MBA)--University of Pretoria, 2015.
pa2016
Gordon Institute of Business Science (GIBS)
MBA
Unrestricted

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Gao, Fei. "Structure based online social network link prediction study." Thesis, King's College London (University of London), 2017. https://kclpure.kcl.ac.uk/portal/en/theses/structure-based-online-social-network-link-prediction-study(41697041-bfe4-4e64-a516-1a0703cfb4bb).html.

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This thesis shed light on the Internet-based social network link prediction problem. After reviewing recent research achievements in this area, two hypotheses are introduced: (i) The performance of topology-based network prediction methods and the characteristics of the networks are correlated. (ii) As networks are dynamic, the performance of prediction can be improved by providing different treatment to different nodes and links. To verify the Hypothesis (i), we conduct experiments with six selected online social networks. The correlation coefficients are calculated between six common network metrics and ten widely used topology-based network link prediction methods. The results show a strong correlation between Gini Coefficient and Preferential Attachment method. This study also reveals two types of networks: prediction-friendly network, for which most of the selected prediction methods perform well with an AUC result above 0.8, and prediction unfriendly network that on the contrary. For Hypothesis (ii), we proposed two network prediction models, the Hybrid Prediction Model and Community Bridge Boosting Prediction Model (CBBPM). The hybrid prediction model assumes network links are formed following different rules. The model linearly combines eight link prediction methods and the evolvement rules have been probed by finding the best weight for each of the methods by solving the linear optimization problem. This experiment result shows an improvement of prediction accuracy. This model takes link prediction as a time series problem. Different from Hybrid Prediction Model, CBBPM provides a different treatment on nodes. We define and classify network nodes as community bridge nodes in a novel approach based on their degree and links position in network communities. The similarity score that is calculated from the selected prediction methods is then boosted for predicting new links. The results from this model also show an enhancement of prediction accuracy. The two hypotheses are validated using the research experiments.

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Weiand, Klara. "Keyword-Based Querying for the Social Semantic Web." Diss., lmu, 2011. http://nbn-resolving.de/urn:nbn:de:bvb:19-126719.

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Muthmann, Klemens. "Topic-Based Aggregation of Questions in Social Media." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-125989.

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Software produced by big companies such as SAP is often feature rich, very expensive and thus only affordable by other big companies. It usually takes months and special trained consultants to install and manage such software. However as vendors move to other market segments, featuring smaller companies, different requirements arise. It is not possible for medium or small sized companies to spend as much money for business software solutions as big companies do. They especially cannot afford to hire expensive consultants. It is on the other hand not economic for the vendor to provide the personnel free of charge. One solution to this dilemma is bundling all customer support cases on special Web platforms, such as customer support forums. SAP for example has the SAP Community Network1. This has the additional benefit that customers may help each other. (...)

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Lim, Choi Keung Sarah Niukyun. "Trust-based social mechanism to counter deceptive behaviour." Thesis, University of Warwick, 2011. http://wrap.warwick.ac.uk/38163/.

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The actions of an autonomous agent are driven by its individual goals and its knowledge and beliefs about its environment. As agents can be assumed to be selfinterested, they strive to achieve their own interests and therefore their behaviour can sometimes be difficult to predict. However, some behaviour trends can be observed and used to predict the future behaviour of agents, based on their past behaviour. This is useful for agents to minimise the uncertainty of interactions and ensure more successful transactions. Furthermore, uncertainty can originate from malicious behaviour, in the form of collusion, for example. Agents need to be able to cope with this to maximise their benefits and reduce poor interactions with collusive agents. This thesis provides a mechanism to support countering deceptive behaviour by enabling agents to model their agent environment, as well as their trust in the agents they interact with, while using the data they already gather during routine agent interactions. As agents interact with one another to achieve the goals they cannot achieve alone, they gather information for modelling the trust and reputation of interaction partners. The main aim of our trust and reputation model is to enable agents to select the most trustworthy partners to ensure successful transactions, while gathering a rich set of interaction and recommendation information. This rich set of information can be used for modelling the agents' social networks. Decentralised systems allow agents to control and manage their own actions, but this suffers from limiting the agents' view to only local interactions. However, the representation of the social networks helps extend an agent's view and thus extract valuable information from its environment. This thesis presents how agents can build such a model of their agent networks and use it to extract information for analysis on the issue of collusion detection.

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Rawashdeh, Majdi. "Towards Folksonomy-based Personalized Services in Social Media." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/30985.

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Every single day, lots of users actively participate in social media sites (e.g., Facebook, YouTube, Last.fm, Flicker, etc.) upload photos, videos, share bookmarks, write blogs and annotate/comment on content provided by others. With the recent proliferation of social media sites, users are overwhelmed by the huge amount of available content. Therefore, organizing and retrieving appropriate multimedia content is becoming an increasingly important and challenging task. This challenging task led a number of research communities to concentrate on social tagging systems (also known as folksonomy) that allow users to freely annotate their media items (e.g., music, images, or video) with any sort of arbitrary words, referred to as tags. Tags assist users to organize their own content, as well as to find relevant content shared by other users. In this thesis, we first analyze how useful a folksonomy is for improving personalized services such as tag recommendation, tag-based search and item annotation. We then propose two new algorithms for social media retrieval and tag recommendation respectively. The first algorithm computes the latent preferences of tags for users from other similar tags, as well as latent annotations of tags for items from other similar items. We then seamlessly map the tags onto items, depending on an individual user’s query, to find the most desirable content relevant to the user’s needs. The second algorithm improves tag-recommendation and item annotation by adapting the Katz measure, a path-ensemble based proximity measure, for the use in social tagging systems. In this algorithm we model folksonomy as a weighted, undirected tripartite graph. We then apply the Katz measure to this graph, and exploit it to provide personalized tag recommendation for individual users. We evaluate our algorithms on two real-world folksonomies collected from Last.fm and CiteULike. The experimental results demonstrate that the proposed algorithms improve the search and the recommendation performance, and obtain significant gains in cold start situations where relatively little information is known about a user or an item

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Jones, Simon. "Automating group-based privacy control in social networks." Thesis, University of Bath, 2012. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.629649.

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Users of social networking services such as Facebook often want to manage the sharing of information and content with diﬀerent groups of people based on their diﬀering relationships. The growing popularity of such services has meant that users are increasingly faced with the copresence of diﬀerent groups associated with diﬀerent aspects of their lives, within their network of contacts. However, few users are utilising the group-based privacy controls provided to them by the SNS provider. In this thesis we examine the reasons behind the lack of use of group-based privacy controls, ﬁnding that it can be largely attributed to the signiﬁcant burden associated with group conﬁguration. We aim to overcome this burden by developing automated mechanisms to assist users with many aspects of group-based privacy control, including initial group conﬁguration, labeling, adjustment and selection of groups for sharing privacy sensitive content. We use a mixed methods approach in order to understand: how automated mechanisms should be designed in order to support users with their privacy control, how well these mechanisms can be expected to work, what the limitations are, and how such mechanisms aﬀect users’ experiences with social networking services and content sharing. Our results reveal the criteria that SNS users employ in order to conﬁgure their groups for privacy control and illustrate that oﬀ-the-shelf algorithms and techniques which are analogous to these criteria can be used to support users. We show that structural network clustering algorithms provide beneﬁts for initial group conﬁguration and that clustering threshold adjustments and detection of hubs and outliers with the network are necessary for group adjustment. We demonstrate that public proﬁle data can be extracted from the network in order to help users to comprehend their groups, and that contextual information relating to context, contacts, and content can be used to make recommendations about which groups might be useful for disclosure in a given situation. We also show that all of these mechanisms can be used to signiﬁcantly reduce the burden of privacy control and that users react positively to such features.

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Caeyers, Bet Helena. "Social networks, community-based development and empirical methodologies." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:61dbdd9e-9341-4959-a6ca-15547720df3c.

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This thesis consists of two parts: Part I (Chapters 2 and 3) critically assesses a set of methodological tools that are widely used in the literature and that are applied to the empirical analysis in Part II (Chapters 4 and 5). Using a randomised experiment, the first chapter compares pen-and-paper interviewing (PAPI) with computer-assisted personal interviewing (CAPI). We observe a large error count in PAPI, which is likely to introduce sample bias. We examine the effect of PAPI consumption measurement error on poverty analysis and compare both applications in terms of interview length, costs and respondents’ perceptions. Next, we formalise an unproven source of ordinary least squares estimation bias in standard linear-in-means peer effects models. Deriving a formula for the magnitude of the bias, we discuss its underlying parameters. We show when the bias is aggravated in models adding cluster fixed effects and how it affects inference and interpretation of estimation results. We reveal that two-stage least squares (2SLS) estimation strategies eliminate the bias and provide illustrative simulations. The results may explain some counter-intuitive findings in the social interaction literature. We then use the linear-in-means model to estimate endogenous peer effects on the awareness of a community-based development programme of vulnerable groups in rural Tanzania. We denote the geographically nearest neighbours set as the relevant peer group in this context and employ a popular 2SLS estimation strategy on a unique spatial household dataset, collected using CAPI, to identify significant average and heterogeneous endogenous peer effects. The final chapter investigates social network effects in decentralised food aid (free food and food for work) allocation processes in Ethiopia, in the aftermath of a serious drought. We find that food aid is responsive to need, as well as being targeted at households with less access to informal support. However, we also find strong correlations with political connections, especially in the immediate aftermath of the drought.

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Wangchuk, Tshering. "Community-based Influence Maximization framework for Social Networks." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15378.

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Maximizing Influence (IM) in social networks has a considerable role to play in the phenomenon of viral marketing, targeted advertisements and in promoting any campaigns. However, the Influence Maximization Problem is a very challenging research-problem due to it being NP-Hard and scaling with the social networks with millions of nodes and edges becomes very tough due to the computational complexities concerned with it. Recently, solving this problem through the use of community detection based methodology is becoming very popular since, it reduces the search space by dividing the network into smaller and more manageable groups called "communities." As part of the larger research work, we reiterate a framework which has been inspired by collection of different work done by Alfalahi et al. (2013) that we can implement to solve the IM problem and its limitation through community detection and fuzzy logic inspired approach. Since the work is still under development, for this project, we report on understanding the IM field through literature reviews and in communicating a design of IM framework as inspired by the previous works. We also present our version ofthe blueprint (Algorithm design) of the framework as a five step approach. For the purpose of this report, we implement and evaluated the step 1 and step 2 of the framework. Step 1 is about preprocessing the input network with a similarity measure, which according to previous study by Alfalahi et al. (2013a) aids the algorithms in detecting better community structure (clear and accurate distinction of the nodes into communities in networks). We test it to see if it holds true. Step 2 is about implementing the community detection in social network. We benchmarkthree candidate algorithms, chosen based on theirperformance, from the previous studies in community detection fieldand we report onwhich algorithm should we consider to use in the proposed framework through experimentationon the simulated data. We use Normalized Mutual Information (NMI) and Modularity (Q) as evaluation metrics to measure the accuracy of the community detected by the candidate algorithms. Our results show that similarity based preprocessing does not improve the community structure and thus may not be required in the framework. We also found out that Louvain should be the algorithm that use to detect communities in social networks since it outperforms both CNM and Infomap on Q and NMI

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Rebaza, Jorge Carlos Valverde. "Mining user behavior in location-based social networks." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-16112017-085356/.

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Online social networks (OSNs) are Web platforms providing different services to facilitate social interaction among their users. A particular kind of OSNs is the location-based social network (LBSN), which adds services based on location. One of the most important challenges in LBSNs is the link prediction problem. Link prediction problem aims to estimate the likelihood of the existence of future friendships among user pairs. Most of the existing studies in link prediction focus on the use of a single information source to perform predictions, i.e. only social information (e.g. social neighborhood) or only location information (e.g. common visited places). However, some researches have shown that the combination of different information sources can lead to more accurate predictions. In this sense, in this thesis we propose different link prediction methods based on the use of different information sources naturally existing in these networks. Thus, we propose seven new link prediction methods using the information related to user membership in social overlapping groups: common neighbors within and outside of common groups (WOCG), common neighbors of groups (CNG), common neighbors with total and partial overlapping of groups (TPOG), group naïve Bayes (GNB), group naïve Bayes of common neighbors (GNB-CN), group naïve Bayes of Adamic-Adar (GNB-AA) and group naïve Bayes of Resource Allocation (GNB-RA). Due to that social groups exist naturally in networks, our proposals can be used in any type of OSN.We also propose new eight link prediction methods combining location and social information: Check-in Observation (ChO), Check-in Allocation (ChA), Within and Outside of Common Places (WOCP), Common Neighbors of Places (CNP), Total and Partial Overlapping of Places (TPOP), Friend Allocation Within Common Places (FAW), Common Neighbors of Nearby Places (CNNP) and Nearby Distance Allocation (NDA). These eight methods are exclusively for work in LBSNs. Obtained results indicate that our proposals are as competitive as state-of-the-art methods, or better than they in certain scenarios. Moreover, since our proposals tend to be computationally more efficient, they are more suitable for real-world applications.
Redes sociais online (OSNs) são plataformas Web que oferecem serviços para promoção da interação social entre usuários. OSNs que adicionam serviços relacionados à geolocalização são chamadas redes sociais baseadas em localização (LBSNs). Um dos maiores desafios na análise de LBSNs é a predição de links. A predição de links refere-se ao problema de estimar a probabilidade de conexão futura entre pares de usuários que não se conhecem. Grande parte das pesquisas que focam nesse problema exploram o uso, de maneira isolada, de informações sociais (e.g. amigos em comum) ou de localização (e.g. locais comuns visitados). Porém, algumas pesquisas mostraram que a combinação de diferentes fontes de informação pode influenciar o incremento da acurácia da predição. Motivado por essa lacuna, neste trabalho foram desenvolvidos diferentes métodos para predição de links combinando diferentes fontes de informação. Assim, propomos sete métodos que usam a informação relacionada à participação simultânea de usuários en múltiples grupos sociais: common neighbors within and outside of common groups (WOCG), common neighbors of groups (CNG), common neighbors with total and partial overlapping of groups (TPOG), group naïve Bayes (GNB), group naïve Bayes of common neighbors (GNB-CN), group naïve Bayes of Adamic-Adar (GNB-AA), e group naïve Bayes of Resource Allocation (GNB-RA). Devido ao fato que a presença de grupos sociais não está restrita a alguns tipo de redes, essas propostas podem ser usadas nas diversas OSNs existentes, incluindo LBSNs. Também, propomos oito métodos que combinam o uso de informações sociais e de localização: Check-in Observation (ChO), Check-in Allocation (ChA), Within and Outside of Common Places (WOCP), Common Neighbors of Places (CNP), Total and Partial Overlapping of Places (TPOP), Friend Allocation Within Common Places (FAW), Common Neighbors of Nearby Places (CNNP), e Nearby Distance Allocation (NDA). Tais propostas são para uso exclusivo em LBSNs. Os resultados obtidos indicam que nossas propostas são tão competitivas quanto métodos do estado da arte, podendo até superá-los em determinados cenários. Ainda mais, devido a que na maioria dos casos nossas propostas são computacionalmente mais eficientes, seu uso resulta mais adequado em aplicações do mundo real.

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Bohn, Angela, Ingo Feinerer, Kurt Hornik, and Patrick Mair. "Content-Based Social Network Analysis of Mailing Lists." The R Foundation for Statistical Computing, 2011. http://epub.wu.ac.at/5435/1/RJournal_2011%2D1_Bohn~et~al.pdf.

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Social Network Analysis (SNA) provides tools to examine relationships between people. Text Mining (TM) allows capturing the text they produce inWeb 2.0 applications, for example, however it neglects their social structure. This paper applies an approach to combine the two methods named "content-based SNA". Using the R mailing lists, R-help and R-devel, we show how this combination can be used to describe people's interests and to find out if authors who have similar interests actually communicate. We find that the expected positive relationship between sharing interests and communicating gets stronger as the centrality scores of authors in the communication networks increase.

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Li, Yafei. "Efficient group queries in location-based social networks." HKBU Institutional Repository, 2015. https://repository.hkbu.edu.hk/etd_oa/203.

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Nowadays, with the rapid development of GPS-equipped mobile devices, location-based social networks have been emerging to bridge the gap between the physical world and online social networking services. Various types of data, such as personal locations, check-ins, microblogs and social relations, have been available in location-based social networks. Efficiently managing and analyzing such data to meet users' daily query requirements become a challenging task. Among all the existing works in location-based social networks, group query is one of the most important research topics. In this thesis, we investigate query techniques for location-based services in social networking applications. Specifically, considering a location-based social network, we study spatial-aware interest group queries, geo-social {dollar}k{dollar}-cover group queries, and social-aware ridesharing group queries. Firstly, we study the spatial-aware interest group queries in location-based social networks. Recently, most of the location-based social networks release check-in services that allow users to share their visiting locations with their friends. These locations, considered as spatial objects, are usually associated with a few tags that describe the features of those locations. Utilizing such information, we propose a new type of \emph{Spatial-aware Interest Group} (SIG) query that retrieves a user group of size {dollar}k{dollar} where each user is interested in the query keywords and the users are close to each other in the Euclidean space. We prove this query problem is NP-complete, and develop two efficient algorithms IOAIR and DOAIR based on the IR-tree for the processing of SIG queries. We also validate the performance efficiency of the proposed query processing algorithms by empirical evaluation. Secondly, we study the problem of geo-social {dollar}k{dollar}-cover group queries for collaborative spatial computing. In this problem, we propose a novel type of geo-social queries, called \emph{Geo-Social K-Cover Group} (GSKCG) query, which is based on spatial containment and a new modeling of social relationships. Intuitively, given a set of spatial query points and an underlying social network, a GSKCG query finds a minimum user group in which the members satisfy certain social relationship and their associated regions can jointly cover all the query points. Albeit its practical usefulness, the GSKCG query problem is NP-complete. We consequently explore a set of effective pruning strategies to derive an efficient algorithm for finding the optimal solution. Moreover, we design a novel index structure tailored to our problem to further accelerate query processing. Extensive experiments demonstrate that our algorithm achieves desirable performance on real-life datasets. Thirdly, we study the problem of social-aware ridesharing group queries. With the deep penetration of smartphones and geo-locating devices, ridesharing is envisioned as a promising solution to transportation-related problems such as congestion and air pollution for metropolitan cities. Despite the potential to provide significant societal and environmental benefits, ridesharing has not so far been as popular as expected. Notable barriers include the social discomfort and safety concerns when traveling with strangers. To overcome these barriers, in this thesis, we propose a new type of \emph{Social-aware Ridesharing Group} (SaRG) query which retrieves a group of riders by taking into account their social connections besides traditional spatial proximities. Because the SaRG query problem is NP-hard, we design an efficient algorithm with a set of powerful pruning techniques to tackle this problem. We also present several incremental strategies to accelerate the search speed by reducing the repeated computations. Moreover, we propose a novel index tailored to the proposed problem to further speed up the query processing. Experimental results on real datasets show that our proposed algorithms achieve desirable performance. The works of this thesis show that the group query processing techniques are effective, which would facilitate the wider deployment of such query services in real applications

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Henry, Nathalie. "Exploring large social networks with matrix-based representations." Paris 11, 2008. http://www.theses.fr/2008PA112237.

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Grâce à la banalisation des outils de communication électroniques, les chercheurs en sciences sociales disposent de nombreuses données. Les communautés en ligne telles que Facebook et Flickr par exemple, fournissent de riches informations sur la façon dont les personnes communiquent et l’évolution de leurs réseaux sociaux. Pour analyser ces données, les sociologues ont besoin d’outils robustes, pouvant manipuler de grandes quantités de données, et flexibles, permettant l’exploration a de multiples niveaux : de la vue d’ensemble a l’analyse détaillée d’une sous partie. Nous proposons de visualiser les données car le cerveau humain est très efficace pour traiter les informations visuelles. La majorité des outils de visualisation de réseaux sont basés sur des diagrammes nœuds-liens. Ces représentations ayant d’importants problèmes de lisibilités, nous explorons dans cette thèse des représentations alternatives basées sur des matrices d’adjacence. Nous présentons trois systèmes interactifs conçus avec des chercheurs en sciences sociales : MatrixExplorer, MatLink et NodeTrix. MatrixExplorer combine matrices et nœuds-liens. Les deux représentations sont synchronisées et un panel d’outils interactifs permet de les manipuler. MatLink est une matrice augmentée de liens interactifs, qui permettent de mieux percevoir la connectivité du réseau. Enfin NodeTrix représente les réseaux par des diagrammes nœuds-liens et leurs parties denses par des matrices. NodeTrix est particulièrement efficace pour des réseaux petit-monde. Cette thèse présente la conception et l’évaluation de ces trois systèmes ainsi qu’une étude de cas analysant 20 ans de publications en Interaction Homme-Machine
With the increasing use of Internet technologies, social scientists have more data to analyze. Online communities such as Facebook or Flickr provide rich information on how people communicate and how their social network evolves. To analyze this data, social scientists require robust tools that can handle large and complex networks and allow a flexible analysis from overviews of the entire dataset to detailed analysis of important sections. As human brain is particularly effective at processing visual information, we propose to support the exploration of social networks by information visualization. Previous tools for network visualization are mostly based on node-link diagrams, suffering of readability issues (node overlapping or edge crossing) for either large or dense networks. In this thesis, we investigate alternative representations based on adjacency matrices. Following participatory design principles, we involved social scientists into the design of three interactive visual systems: MatrixExplorer, MatLink and NodeTrix. MatrixExplorer combines matrices and node-link diagrams. Both representations are coordinated and a set of interactive tools allows their manipulation. MatLink is an augmented matrix, providing interactive links on its border to help performing some connectivity tasks. Finally, NodeTrix represents networks as node-link diagrams, using matrices for dense sub-parts. NodeTrix is particularly suited for small-world networks, globally sparse but locally dense. This dissertation presents the design and evaluation of these three systems including a case study analyzing 20 years of publications data in Human-Computer Interaction

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St, Amand Santos Monica. "Generalization of Social Skills Based on Instructional Setting." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/6129.

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Children with social skills deficits in verbal and nonverbal communication can face a variety of social challenges in many aspects of their lives. Given the increasing social needs of many students in today's classrooms, there is a need for increased social skills instruction and support in public schools. Inclusion opportunities in public schools can have a positive impact on the development of social skills and can increase peer understanding and empathy for students with special needs. Although there is research in the area of inclusion and its benefits, there is little known about the impact of the instructional setting on the ability of children to generalize social skills to other school settings. Based on social development theory and social learning theory, this quantitative study used secondary data (N = 129) from 2 primary schools in Connecticut to determine whether elementary age children are more likely to generalize social skills if they are taught social skills in the general education classroom setting compared to those who are taught social skills in the resource room setting or receive no instruction in social skills controlling for natural social skills growth. The result of an ANCOVA revealed that children who were taught social skills in the general education setting were more likely to generalize social skills across settings. The results of this study contribute to positive social change by helping inform school administrators and teachers about how to best support children with social deficits in reaching their academic and social potential. The findings may also help to create an environment that is more accepting of the varying needs of students and as a result can help to create a positive school climate and increase acceptance and friendships among elementary age students that can last into adulthood.

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Cordeiro, João Miguel Magalhães Marcelino Fernandes. "Sound based social networks." Doctoral thesis, 2013. http://hdl.handle.net/10400.14/15773.

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The sound environment is an eco of the activity and character of each place, often carrying additional information to that made available to the eyes (both new and redundant). It is, therefore, an intangible and volatile acoustic fingerprint of the place, or simply an acoustic snapshot of a single event. Such rich resource, full of meaning and subtleness, Schaeffer called Soundscape. The exploratory research project presented here addresses the Soundscape in the context of Mobile Online Social Networking, aiming at determining the extent of its applicability regarding the establishment and/or strengthening of new and existing social links. Such research goal demanded an interdisciplinary approach, which we have anchored in three main stems: Soundscapes, Mobile Sound and Social Networking. These three areas pave the scientific ground for this study and are introduced during the first part of the thesis. An extensive survey of the state-of-the-arte projects related with this research is also presented, gathering examples from different but adjacent areas such as mobile sensing, wearable computing, sonification, social media and contextaware computing. This survey validates that our approach is scientifically opportune and unique, at the same time. Furthermore, in order to assess the role of Soundscapes in the context of Social Networking, an experimental procedure has been implemented based on an Online Social Networking mobile application, enriched with environmental sensing mechanisms, able to capture and analyze the surrounding Soundscape and users' movements. Two main goals guided this prototypal research tool: collecting data regarding users' activity (both sonic and kinetic) and providing users with a real experience using a Sound-Based Social Network, in order to collect informed opinions about this unique type of Social Networking. The application – Hurly-Burly – senses the surrounding Soundscape and analyzes it using machine audition techniques, classifying it according to four categories: speech, music, environmental sounds and silence. Additionally, it determines the sound pressure level of the sensed Soundscape in dB(A)eq. This information is then broadcasted to the entire online social network of the user, allowing each element to visualize and audition a representation of the collected data. An individual record for each user is kept available in a webserver and can be accessed through an online application, displaying the continuous acoustic profile of each user along a timeline graph. The experimental procedure included three different test groups, forming each one a social network with a cluster coefficient equal to one. After the implementation and result analysis stages we concluded that Soundscapes can have a role in the Online Social Networking paradigm, specially when concerning mobile applications. Has been proven that current offthe- shelf mobile technology is a promising opportunity for accomplishing this kind of tasks (such as continuous monitoring, life logging and environment sensing) but battery limitations and multitasking's constraints are still the bottleneck, hindering the massification of successful applications. Additionally, online privacy is something that users are not enthusiastic in letting go: using captured sound instead of representations of the sound would abstain users from utilizing such applications. We also demonstrated that users who are more aware of the Soundscape concept are also more inclined to assume it as playing an important role in OSN. This means that more pedagogy towards the acoustic phenomenon is needed and this type of research gives a step further in that direction.
O ambiente sonoro de um lugar é um eco da sua atividade e carácter, transportando, na maior parte da vezes, informação adicional àquela que é proporcionada à visão (quer seja redundante ou complementar). É, portanto, uma impressão digital acústica - tangível e volátil - do lugar a que pertence, ou simplesmente uma fotografia acústica de um evento pontual. A este opulento recurso, carregado de significados e subtilezas, Schafer chamou de Paisagem-Sonora. O projeto de investigação de carácter exploratório que aqui apresentamos visa o estudo da Paisagem-Sonora no contexto das Redes Sociais Móveis Em-Linha, procurando entender os moldes e limites da sua aplicação, tendo em vista o estabelecimento e/ou reforço de novos ou existente laços sociais, respectivamente. Para satisfazer este objectivo foi necessária uma abordagem multidisciplinar, ancorada em três pilares principais: a Paisagem-Sonora, o Som Móvel e as Redes Sociais. Estas três áreas determinaram a moldura científica de referência em que se enquadrou esta investigação, sendo explanadas na primeira parte da tese. Um extenso levantamento do estado-da-arte referente a projetos relacionados com este estudo é também apresentado, compilando exemplos de áreas distintas mas adjacentes, tais como: Computação Sensorial Móvel, Computação Vestível, Sonificação, Média Social e Computação Contexto-Dependente. Este levantamento veio confirmar quer a originalidade quer a pertinência científica do projeto apresentado. Posteriormente, a fim de avaliar o papel da Paisagem-Sonora no contexto das Redes Sociais, foi posto em prática um procedimento experimental baseado numa Rede Social Sonora Em-Linha, desenvolvida de raiz para dispositivos móveis e acrescida de mecanismos sensoriais para estímulos ambientais, capazes de analisar a Paisagem-Sonora envolvente e os movimentos do utilizador. Dois objectivos principais guiaram a produção desta ferramenta de investigação: recolher dados relativos à atividade cinética e sonora dos utilizadores e proporcionar a estes uma experiência real de utilização uma Rede Social Sonora, de modo a recolher opiniões fundamentadas sobre esta tipologia específica de socialização. A aplicação – Hurly-Burly – analisa a Paisagem-Sonora através de algoritmos de Audição Computacional, classificando- a de acordo com quatro categorias: diálogo (voz), música, sons ambientais (“ruídos”) e silêncio. Adicionalmente, determina o seu nível de pressão sonora em dB(A)eq. Esta informação é então distribuída pela rede social dos utilizadores, permitindo a cada elemento visualizar e ouvir uma representação do som analisado. É mantido num servidor Web um registo individual da informação sonora e cinética captada, o qual pode ser acedido através de uma aplicação Web que mostra o perfil sonoro de cada utilizador ao longo do tempo, numa visualização ao estilo linha-temporal. O procedimento experimental incluiu três grupos de teste distintos, formando cada um a sua própria rede social com coeficiente de aglomeração igual a um. Após a implementação da experiência e análise de resultados, concluímos que a Paisagem- Sonora pode desempenhar um papel no paradigma das Redes Sociais Em- Linha, em particular no que diz respeito à sua presença nos dispositivos móveis. Ficou provado que os dispositivos móveis comerciais da atualidade apresentam-se com uma oportunidade promissora para desempenhar este tipo de tarefas (tais como: monitorização contínua, registo quotidiano e análise sensorial ambiental), mas as limitações relacionadas com a autonomia energética e funcionamento em multitarefa representam ainda um constrangimento que impede a sua massificação. Além disso, a privacidade no mundo virtual é algo que os utilizadores atuais não estão dispostos a abdicar: partilhar continuamente a Paisagem-Sonora real em detrimento de uma representação de alto nível é algo que refrearia os utilizadores de usar a aplicação. Também demonstrámos que os utilizadores que mais conhecedores do fenómeno da Paisagem-Sonora são também os que consideram esta como importante no contexto das Redes Sociais Em-Linha. Isso significa que uma atitude pedagógica em relação ao fenómeno sonoro é essencial para obter dele o maior ganho possível. Esta investigação propõe-se a dar um passo em frente nessa direção.

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Wen, Yu-Ting, and 溫郁婷. "Exploring social influence on location-based social networks." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/99336810230166308365.

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碩士
國立交通大學
資訊科學與工程研究所
102
Recently, with the advent of location-based social networking services (LBSNs), e.g., Foursquare, Yelp, Geolife and Flickr, travel planing and location-aware information recommendation based on LBSN have attracted research attentions, such as Point-of-interest (POI) recommendation or travel routes recommendation. Most of the existing works mainly address on mining POIs by crowd power in LBSN and generate the recommendation on demand. For example, extracting personal preferences from individual’s location history to score the POIs in query region. However, they ignore the impact of social relations hidden in LBSN, i.e., the social influence from friends. We suppose that the location-aware recommendation with favorable comments from friends should be more reliable than that from unfamiliar crowd.In this paper, we propose a new social influence-based user recommender framework (SIR) which differs from prior works by aiming to discover the potential value addition from reliable users (i.e. close friends and travel experts). Explicitly, our SIR framework is able to infer influential users from LBSN. We claim to capture the interaction among virtual community, physical mobility activities and time effects to infer the social influence between user pairs. Furthetmore, we intend to model the propagation of influence in terms of diffusion-based mechanism. Third, we design a dynamic fusion framework to integrate the features mined into an united follow probability score. Finally, our framework provides personalized top-k user recommendation for individuals. To evaluate the recommendation results, we conduct extensive experiments on real datasets (i.e., Flicker dataset and Gowalla datasets). The experimental results shows the performance of our SIR framework is better than a state-of-the-art user recommendation mechanisms in terms of accuracy and reliability.

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Cheng, Song-Fen, and 鄭松棻. "Recommended based on Social Behavior." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/03451460854176891878.

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碩士
淡江大學
資訊工程學系碩士在職專班
98
Pushed by the increasing advancement of computer technology and the rapid growth of the Internet, digital information has been produced on a mass scale. Internet network has become a huge information source and provided rich and valuable resource. Every Web site is like a data source, and these sources can be seen as a database in general sense, even large and more complex than the database in conventional sense. Via website links, these Web sites with different contents and organizations constitute a large heterogeneous database environment. Without the help of efficient search engines, finding the wanted information from the current World Wide Web will be as difficult as looking for a needle in the haystack. Today there are many commercial search engines to meet such needs, for instance: Google, Yahoo, Ask and Microsoft Live Search, and so on. Search engines usually will rate and list the searched results according to their relevancy for users to browse and choose the summary contents of the searched results. Such a browsing mode is extremely inefficient, since the quantity of web search results is usually quite huge and most general users only browse a number of searched results listed in the beginning. Besides, this kind of rating and listing would make a lot of sub-topics searched mixed up with the wanted ones. This also tends to cause users to miss important information. In addition, in the process of retrieval, many users usually do not keep conducting keyword searches but instead spending more time browsing the searched results. However, a major problem is that the search engines using the search mechanism of web contents and hyperlink mode can only reflect web authors’ views but not readers’. In this paper, we based on users’ browsing web contents to develop web user clustering mining technology. And according to our experimental results, users can classify the web contents (of the websites browsed by them) and apply those contents to the web recommendation through the websites browsed by them.

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JHENG, KAI-JHONG, and 鄭凱中. "A Beacon-Based Social System." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/96zyk6.

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碩士
國立中正大學
資訊工程研究所
106
In recent years, the social network and social software have grown substantially. The Weibo, twitter, Facebook, Line, and We Chat provides more service that makes information exchange between people more convenient. There were much social software on the network and the threshold of registering accounts is getting lower that making many fake accounts and the proliferation of pornographic advertising, in addition, it may cause problems, such as Internet fraud, personal safety and erotic trap, in fact, some people had suffered because they make wrong friends on the network. Therefore, with such diverse social networks and social software in the community, making friends is an important issue that must be given due attention. The goal of this study is to establish a regional social system that is immediacy and regional, and removes the shortcomings associated with pairing to create an excellent social environment. The environment of the system is built on the mobile application and incorporates a beacon. With this system, the user information is pushed to this range when the user is in the beacon push range, the system will perform user pairing through similarity algorithm that range can be adjusted according to the square meters. In addition, we also use the miniature positioning technology to locate the paired successful users and allow users to meet. Here we propose a regional social system that has immediacy and regional features that enhance user experience and ensure user safety. The system can be set in general indoor, can also be set in public places, such as parks, train station, plaza.

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Chuang, Ching-hao, and 莊清皓. "Community Detection - Based on Social Interactions in Social Network." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/27471568342387395387.

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碩士
國立中央大學
資訊管理研究所
100
There has been much recent research about identifying communities in networks. Based on the online social network, which is getting more and more popular recently, we explore the community detection problem, i.e., how to identify the hidden sub-groups in the heterogeneous social network. Traditional research on community detection usually assumed that the structural information of the network is fully known, which is not feasible for many practical networks. Moreover, most previous algorithms for community detection did not differentiate multiple relations existing among objects or persons in a real world. In Facebook, two persons can be either friend or not friend. But in reality a friend relation may come from different reasons and belong to different social groups. Thus, how to differentiate different relations among users on Facebook is a key research issue in our work. In this paper, we propose a new approach utilizing the social interaction data, rather than structural information of the network, to address the community detection problem in Facebook. Specifically, we develop a method to find the multiple social groups of a Facebook user from his/her past interaction data with friends. The advantages of our approach include: i) it does not depend on the structural information, ii) it can differentiate different relations existing among friends, iii) it allows a friend belonging to multiple communities at the same time. In the experiment, we retrieve 10 Facebook user’s data as our datasets and evaluate the performance of each dataset. The results show that our method can identify the hidden social groups of users successfully from the interaction data in Facebook. Experimental results verify the feasibility and effectiveness of our approach.

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47

Gramling, Jennifer Lynn. "Students' experiences of the social environment and social presence in campus-based and web-based education." 2003. http://etd.utk.edu/2003/GramlingJennifer.pdf.

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Thesis (Ph. D.)--University of Tennessee, Knoxville, 2003.
Title from title page screen (viewed Sept. 24, 2003). Thesis advisor: John R. Ray. Document formatted into pages (ix, 129 p. : ill. (some col.)). Vita. Includes bibliographical references (p. 95-107).

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48

Tung, Kuan Chieh, and 童冠傑. "Predicting Elections Based on Social Media." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/04571503441843228679.

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碩士
國立清華大學
資訊系統與應用研究所
103
Election prediction has been studied in the recent years. However, the previous works focus on counting the number of tweets mentioning candidates to predict the election result. Many reasons cause candidates to win or lose in an election, such as political opinions, social issues, scandals and other reasons. In this paper, we consider a novel viewpoint to predict election results. For a candidate, if the following event sequence happened, “(big event, positive) → (small event, negative) → (big event, positive)”, this candidate will win the election. We consider four approaches to generate the above sequences and then apply the rule-based classifier for predict the election results. A series of experiments are performed to evaluate our approaches and the experiment results reveal that the accuracy of our approaches on predicting election results is over 80% in most of the cases.

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49

Yang, Fu-Chen, and 楊富丞. "Topic-Based Affective Social Media Mining." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/90141990220851072356.

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博士
國立臺灣大學
資訊管理學研究所
104
Online social networks expedite social interactions where people create, share or exchange information and ideas. The contents generated by users in a social network usually contain a large volume of user opinions and feelings. They can be used as an effective vehicle to analyze product preferences, business strategies, marketing campaigns, social events, political movements, and healthcare experiences. Therefore, in this dissertation, we propose three LDA-based methods, called MPM (Mining Perceptual Maps), MAE (Mining Arousing Events) and MSS (Mining Social Support), to mine affective social media in social networks. The MPM method automatically builds perceptual maps and radar charts from consumer reviews based on users’ sentiment polarities toward different product features. Mining perceptual maps and radar charts can help companies gain knowledge of their and competitors’ products. The MAE method extracts emotionally arousing events from a collection of news documents based on readers’ emotions and intensities, where every news document contains a news article and some readers’ comments. Mining emotionally arousing events may provide a quick reference for politicians and a new aspect for hot news recommendation for readers. The MSS method mines social support and users’ emotion transitions from online healthcare social media. Mining social support by considering emotion transitions may help us better understand patients’ needs, attitudes and opinions, and provide more appropriate assistance since the changes of emotions often coincide with the changes of attitudes. Experimental results show that the MPM method can find the strengths and weaknesses of various mobile phones of different brands and different levels of prices from consumer reviews. The MAE method can better predict the readers’ emotions and intensities for unseen news articles, and discover better-quality and more subtle events using intensity. The MSS method shows that people with different diseases may express very different negative emotion transitions, and need various types of social support.

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50

Chiu, Wen-Kuan, and 邱文寬. "Social Network Based Tourist Recommendation System." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/43421837965886354843.

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碩士
國立臺灣師範大學
資訊工程學系
102
Facebook is the most influential community platform in the world; according to the statistics officially released by Facebook, up to the third quarter of 2013, the number of active users has reached 1,190 millions. With the growth of users, Facebook has become a producer of Big data, and the vast amount of status updates posted by users, which conceal all kinds of useful information, have triggered many research projects focus on Facebook parameters such as the like count, the group count, etc. This research is based on Facebook communities. Through the analyses of the SCAN clustering algorithm, the users would be able to understand the relationships and connections between their mutual friends as stated in the results of grouping. Besides, the results of grouping have combined the Big Five personality model. By means of Facebook parameters, users can easily find out the personality traits of their friends. In this research, FQL was adopted to obtain the information of users themselves and friends around them for further analyses. When the number of friends is increasing, the SCAN clustering algorithm can improve the efficiency when it comes to grouping manually on Facebook. Lastly, this system has developed an integration with tourist information for the purpose of backpacking, so suitable travel companions will be recommended according to users' travel itineraries..

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Dissertations / Theses on the topic 'Social-based'

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