Gotowe bibliografie tematyczne / Social network

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Gotowa bibliografia na temat „Social network”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 25 lipca 2025

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Artykuły w czasopismach na temat "Social network"

Trevillion, S. "Social work, social networks and network knowledge." British Journal of Social Work 30, no. 4 (2000): 505–17. http://dx.doi.org/10.1093/bjsw/30.4.505.

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Sharma, Anita, and Prashant Salwan. "Network Matters! Revisiting Social Networks." Academy of Management Proceedings 2017, no. 1 (2017): 17317. http://dx.doi.org/10.5465/ambpp.2017.17317abstract.

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Gilles, Robert, Tabitha James, Reza Barkhi, and Dimitrios Diamantaras. "Simulating Social Network Formation." International Journal of Virtual Communities and Social Networking 1, no. 4 (2009): 1–20. http://dx.doi.org/10.4018/jvcsn.2009092201.

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Social networks depict complex systems as graph theoretic models. The study of the formation of such systems (or networks) and the subsequent analysis of the network structures are of great interest. For information systems research and its impact on business practice, the ability to model and simulate a system of individuals interacting to achieve a certain socio-economic goal holds much promise for proper design and use of cyber networks. We use case-based decision theory to formulate a customizable model of information gathering in a social network. In this model, the agents in the network

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Shehu, Shamsu. "Usability Evaluation of Social Network." International Journal of Scientific Engineering and Research 5, no. 7 (2017): 235–38. https://doi.org/10.70729/ijser171637.

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Ashlesha, S. Nagdive, Tugnayat Rajkishor, and Peshkar Atharva. "Social Network Analysis of Terrorist Networks." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 2553–59. https://doi.org/10.35940/ijeat.C5431.029320.

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Terrorist Activities worldwide has led to the development of sophisticated methodologies for analyzing terrorist groups and networks. Ongoing and past research has found that Social Network Analysis (SNA) is most effective method for predictive counter-terrorism. Social Network Analysis (SNA) is an approach towards analyzing the terrorist networks to better understand the underlying structure of a network and to detect key players within the network and their links throughout the network. It is also need of the hour to convert available raw data into valuable information for the purpose of glo

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Jadhav, Pranavati, and Dr Burra Vijaya Babu. "Detection of Community within Social Networks with Diverse Features of Network Analysis." Journal of Advanced Research in Dynamical and Control Systems 11, no. 12-SPECIAL ISSUE (2019): 366–71. http://dx.doi.org/10.5373/jardcs/v11sp12/20193232.

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Usui, Shohei, Fujio Toriumi, Masato Matsuo, Takatsugu Hirayama, and Kenji Mase. "Greedy Network Growth Model of Social Network Service." Journal of Advanced Computational Intelligence and Intelligent Informatics 18, no. 4 (2014): 590–97. http://dx.doi.org/10.20965/jaciii.2014.p0590.

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As new network communication tools are developed, social network services (SNS) such as Facebook and Twitter are becoming part of a social phenomenon globally impacting on society. Many researchers are therefore studying the structure of relationship networks among users. We propose a greedy network growth model that appropriately increases nodes and links while automatically reproducing the target network. We handle a wide range of networks with high expressive ability. Results of experiments showed that we accurately reproduced 92.4% of 189 target networks from real services. The model also

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Zenkovich, K., T. Zhylkybayev, S. Kaysanov, and T. Ustinova. "APPLYING SOCIAL MINING RESULTS FROM OPEN SOCIAL NETWORKS." Bulletin of Shakarim University. Technical Sciences 1, no. 2(14) (2024): 5–10. http://dx.doi.org/10.53360/2788-7995-2024-2(14)-1.

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TThe advent of web-based communities and social networking sites has resulted in a massive amount of social networking data that is embedded with rich sets of meaningful social media knowledge. Social network analysis and the study of social structures using networks and graph theory help to find a systematic method or process for studying social networks. The article reveals the concept of intellectual analysis of social networks. The key aspect of the article is the application of the results of social network analysis to various branches of human activity.Describes the benefits of using Soc

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Lakon, Cynthia M., Yu Zheng, and Cornelia Pechmann. "Social network tie functions of social support and social influence and adult smoking abstinence." PLOS ONE 19, no. 3 (2024): e0296458. http://dx.doi.org/10.1371/journal.pone.0296458.

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Adults’ social network ties serve multiple functions and play prominently in quitting smoking. We examined three types of adults’ egocentric social networks, including family, friends, and friends online to investigate how two network characteristics with major relevance to health behavior, network size and tie closeness, related to the emotional and confidant support and to pro- and anti-smoking social influence these ties may transmit. We also examine whether the social support and social influence constructs related to smoking abstinence. We utilized baseline and 7-day abstinence survey dat

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M., Shankar. "Social Network Analysis." Shanlax International Journal of Commerce 7, S1 (2019): 259–60. https://doi.org/10.5281/zenodo.3451720.

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Social Network analysis is an investigation made on social structures through the use of networks. The field of social network analysis is the dynamic and highly adaptable combination of techniques that let us quantify and recognize the complex structures and flows of relationships, thoughts, and things between people around the world.     Social network analysis has emerged as a critical technique in modern sociology. It has also gained an important following in economics, geography, history, information science, organizational studies, anthropology, biology, demography, commun

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Rozprawy doktorskie na temat "Social network"

Kyrychok, B. V. "Social network." Thesis, Сумський державний університет, 2013. http://essuir.sumdu.edu.ua/handle/123456789/33691.

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Social networking online involves using Websites to share information with others and connect with them by creating a profile that may include a personal Webpage and a blog. Social networking sites allow users to add friends, send messages and comment on others' profile pages. Social networking has many negatives and positives impact. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/33691

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Mannapperuma, Chanaka. "Tangible Social Network System : Visual Markers for Social Network." Thesis, Umeå University, Department of Informatics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-34927.

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<p><em>Tangible social network system is a home-based communication solution specifically designed for elders. Former researches indicate that insufficient communication among elders cause several challenges in their daily activities such as social isolation, loneliness, depression and decreased appetite. In addition, lack of social participation increases the risk of Alzheimer´s (Ligt Enid, 1990). The major cause of these challenges are that elders are increasingly removed from communication technology using emails, text messaging, interact with social network systems and mobile phones due to

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Torchi, Ilaria. "MOBILE SOCIAL NETWORK: dalle RETI SOCIAL al SOCIALE in RETE." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15415/.

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I Mobile Social Network consentono alle persone di connettersi fra di loro, condividere interessi comuni, opinioni, informazioni e media. Il fattore alla base che accomuna tutti i tempi è sempre la relazione: gli uomini hanno il bisogno vitale di stare con gli altri e se per farlo, oltre che scambiando foto e video, si trovassero delle vie concrete per crescere in solidarietà ed aumentare il bene comune? Nasce così il desiderio di affrontare lo studio di questa tesi facendo ricerca ed esplorazione attraverso tre tappe ben precise. Il titolo “MOBILE SOCIAL NETWORK: dalle RETI SOCIAL al SOCIALE

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Araújo, Ricardo Matsumura de. "Memetic networks : problem-solving with social network models." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2010. http://hdl.handle.net/10183/25515.

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Sistemas sociais têm se tornado cada vez mais relevantes para a Ciência da Computação em geral e para a Inteligência Artificial em particular. Tal interesse iniciou-se pela necessidade de analisar-se sistemas baseados em agentes onde a interação social destes agentes pode ter um impacto no resultado esperado. Uma tendência mais recente vem da área de Processamento Social de Informações, Computação Social e outros métodos crowdsourced, que são caracterizados por sistemas de computação compostos de pessoas reais, com um forte componente social na interação entre estas. O conjunto de todas intera

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Schuhart, Russell G. "Hacking social networks examining the viability of using computer network attack against social networks." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion.exe/07Mar%5FSchuhart.pdf.

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Thesis (M.S. in Information Systems and Operations)--Naval Postgraduate School, March 2007.<br>Thesis Advisor(s): David Tucker. "March 2007." Includes bibliographical references (p. 55-56). Also available in print.

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Vallapu, Sai Krishna. "Towards Network False Identity Detection in Online Social Networks." Thesis, Southern Illinois University at Edwardsville, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10246101.

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<p> In this research, we focus on identifying false identities in social networks. We performed a detailed study on different string matching techniques to identify user profiles with real or fake identity. In this thesis, we focus on a specific case study on sex offenders. Sex offenders are not supposed to be online on social networking sites in few states. To identify the existence of offenders in social networks, we ran experiments to compare datasets downloaded from Facebook and offender registries. To identify the most suitable string matching technique to solve this particular problem, w

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You, Bo. "Hub-Network for Distance Computation in Large Social Networks." Kent State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1412601464.

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Sun, Lei. "Mobile Social Network Platform." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-344871.

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The SWiN project is an abbreviation for Social Wireless Network Secure Identification project and it primarily focuses on the security issues of social networks on mobile platforms. This master thesis is a part of the SWiN project from SICS(Swedish Institute of Computer Science) in cooperation with Ericsson and Sony. In this thesis project, we have designed and implemented a social networkingprototype called Friend Finder. This prototype integrates different security solutions such as SAML and GBA to test the performance of them.

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Shaikh, Sajid S. "Computations in social network." [Kent, Ohio] : Kent State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=kent1185560088.

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Papanastasiou, Effrosyni. "Feasibility of Interactions and Network Inference of Online Social Networks." Electronic Thesis or Diss., Sorbonne université, 2024. http://www.theses.fr/2024SORUS173.

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Cette thèse traite du problème de l'inférence de réseau dans le domaine des réseaux sociaux en ligne. L'hypothèse principale des problèmes d'inférence de réseau est que le réseau que nous observons n'est pas celui dont nous avons réellement be-soin. Cela est particulièrement vrai dans l'espace numérique actuel, où l'abondance d'informations s'accompagne généralement d'un manque crucial de fiabilité, sous la forme de bruit et de points manquants dans les données. Cependant, les approches existantes ignorent ou ne garantissent pas l'inférence de réseaux d'une manière qui puisse expliquer les don

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Książki na temat "Social network"

Freeman, Linton. Social Network Analysis. SAGE Publications Ltd, 2008. http://dx.doi.org/10.4135/9781446263464.

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Knoke, David, and Song Yang. Social Network Analysis. SAGE Publications, Inc., 2008. http://dx.doi.org/10.4135/9781412985864.

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Knoke, David. Social network analysis. 2nd ed. Sage Publications, 2008.

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C, Freeman Linton, ed. Social network analysis. SAGE, 2008.

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C, Freeman Linton, ed. Social network analysis. SAGE, 2008.

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Wu, Jiang. Social Network Computing. Springer Nature Singapore, 2025. http://dx.doi.org/10.1007/978-981-97-4084-0.

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Alhajj, Reda, H. Ulrich Hoppe, Tobias Hecking, Piotr Bródka, and Przemyslaw Kazienko, eds. Network Intelligence Meets User Centered Social Media Networks. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-90312-5.

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Abraham, Ajith, Aboul-Ella Hassanien, and Vaclav Sná¿el, eds. Computational Social Network Analysis. Springer London, 2010. http://dx.doi.org/10.1007/978-1-84882-229-0.

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Aggarwal, Charu C., ed. Social Network Data Analytics. Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-8462-3.

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Dong, Yucheng, Zhaogang Ding, and Gang Kou. Social Network DeGroot Model. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0421-7.

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Części książek na temat "Social network"

Klärner, Andreas, and Holger von der Lippe. "Social Network Mechanisms." In Social Networks and Health Inequalities. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97722-1_4.

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AbstractThe influence and significance of social networks in health research are becoming widely discussed. Sociological network research meets the demand for a stronger consideration of “contexts” or the “environment” that influences health and care. Social networks are conceived as a mediating meso-level, which mediates between social macro-structures (e.g., healthcare systems, institutions, and organizations) and individual (not always) rationally acting actors. This perspective offers the possibility to analyze a variety of psychosocial mechanisms. These mechanisms can influence individual

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Aggrawal, Niyati, and Adarsh Anand. "Network Centrality." In Social Networks. CRC Press, 2022. http://dx.doi.org/10.1201/9781003088066-4.

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Aggrawal, Niyati, and Adarsh Anand. "Network Cohesion." In Social Networks. CRC Press, 2022. http://dx.doi.org/10.1201/9781003088066-9.

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Aggrawal, Niyati, and Adarsh Anand. "Network Models." In Social Networks. CRC Press, 2022. http://dx.doi.org/10.1201/9781003088066-3.

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Whitehead, James, and Mike Peckham. "Social Network Analysis." In Network Leadership. Routledge, 2022. http://dx.doi.org/10.4324/9781003092582-17.

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Pignataro, Carlos, and Joe Marcus Clarke. "Network-Embedded Social Network Protocols." In Network-Embedded Management and Applications. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-6769-5_10.

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Kale, Vivek. "Social Networks." In Agile Network Businesses. Auerbach Publications, 2017. http://dx.doi.org/10.4324/9781315368559-21.

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Chambers, Deborah. "Network Society." In New Social Ties. Palgrave Macmillan UK, 2006. http://dx.doi.org/10.1057/9780230627284_7.

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Bastos, Marco. "Network spillover." In Spatializing Social Media. Routledge, 2021. http://dx.doi.org/10.4324/9780429354328-8.

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Eagle, Nathan, and Alex Pentland. "Social Network Computing." In UbiComp 2003: Ubiquitous Computing. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39653-6_23.

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Streszczenia konferencji na temat "Social network"

Kaushik, Nikunj, Prakarti Goel, Sandeep Lal, and Arun Kumar. "UniVibe - College Social Network." In 2024 1st International Conference on Advances in Computing, Communication and Networking (ICAC2N). IEEE, 2024. https://doi.org/10.1109/icac2n63387.2024.10894818.

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Zhang, Daokun, Jie Yin, Xingquan Zhu, and Chengqi Zhang. "User Profile Preserving Social Network Embedding." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/472.

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This paper addresses social network embedding, which aims to embed social network nodes, including user profile information, into a latent low-dimensional space. Most of the existing works on network embedding only consider network structure, but ignore user-generated content that could be potentially helpful in learning a better joint network representation. Different from rich node content in citation networks, user profile information in social networks is useful but noisy, sparse, and incomplete. To properly utilize this information, we propose a new algorithm called User Profile Preservin

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Silvestru, Catalin ionut, Marianernut Lupescu, Virgil Ion, and Ramona camelia Silvestru. "CONCEPT: SOCIAL NETWORK EDUCATIONAL PLATFORM." In eLSE 2017. Carol I National Defence University Publishing House, 2017. http://dx.doi.org/10.12753/2066-026x-17-077.

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Due to the growing involvement of social networks in economic, politic and social aspects of people’s lives and taking into account that social networks represent the main ICT means of socializing, having a steady increase of users each year, we the authors consider that social networks can have a positive impact on education, and also, if combined with educational tools, can be used efficiently in a non-formal and informal educational purpose. Thus, this paper sets out to analyse the current use of social networks in educational purposes in order to understand the impact social networks have

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Perez, Luis G., Beatriz Montes-Berges, and Maria del Rosario Castillo-Mayen. "Boosting social networks in Social Network-Based Recommender System." In 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2011. http://dx.doi.org/10.1109/isda.2011.6121693.

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Zhao, Guofeng, Dan Li, Chuan Xu, Hong Tang, and Shui Yu. "Network dynamics of mobile social networks." In ICC 2014 - 2014 IEEE International Conference on Communications. IEEE, 2014. http://dx.doi.org/10.1109/icc.2014.6883695.

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Zhang, Yuan, and Changhang Wu. "Social network analysis based on social networks journal co-authorship." In 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), edited by M. A. Jabbar and Pascal Lorenz. SPIE, 2024. http://dx.doi.org/10.1117/12.3032912.

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Zhang, Nan (Andy), and Chong (Alex) Wang. "Network Overlap and Network Blurring in Online Social Networks." In 18th International Conference on Enterprise Information Systems. SCITEPRESS - Science and and Technology Publications, 2016. http://dx.doi.org/10.5220/0005911203270332.

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Tapiador, Antonio, Diego Carrera, and Joaquin Salvachua. "Social Stream, a social network framework." In 2012 International Conference on Future Generation Communication Technology (FGCT). IEEE, 2012. http://dx.doi.org/10.1109/fgct.2012.6476557.

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Myers, Seth A., Aneesh Sharma, Pankaj Gupta, and Jimmy Lin. "Information network or social network?" In the 23rd International Conference. ACM Press, 2014. http://dx.doi.org/10.1145/2567948.2576939.

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Ren, Fuxin, Zhongbao Zhang, Jiawei Zhang, et al. "BANANA: when Behavior ANAlysis meets social Network Alignment." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/200.

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Recently, aligning users among different social networks has received significant attention. However, most of the existing studies do not consider users’ behavior information during the aligning procedure and thus still suffer from the poor learning performance. In fact, we observe that social network alignment and behavior analysis can benefit from each other. Motivated by such an observation, we propose to jointly study the social network alignment problem and user behavior analysis problem. We design a novel end-to-end framework named BANANA. In this framework, to leverage behavior analysis

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Raporty organizacyjne na temat "Social network"

Snijders, Tom. Longitudinal Social Network Analysis. Instats Inc., 2024. https://doi.org/10.61700/zimra7qjrsnu11850.

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This three-day workshop provides an introductory overview of longitudinal social network analysis using the RSiena package, focusing on the application of Stochastic Actor-oriented Models to study network dynamics and the co-evolution of networks and behavior. Participants will gain practical skills in modeling network panel data, as well as modeling co-evolution of networks and behavior, for application of these techniques across various academic disciplines.

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Fernandez, Jasmine, Michaela Bonnett, Teri Garstka, and Meaghan Kennedy. Exploring Social Care Network Structures. Orange Sparkle Ball, 2024. http://dx.doi.org/10.61152/hdnz4028https://www.orangesparkleball.com/innovation-library-blog/2024/5/30/sunbelt2024-exploring-social-care-network-structures.

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This research is grounded in the theory that scale-free networks form between many organizations in a community when coordinating social care services and influential hubs in the network emerge (Barabási & Réka, 1999).We explore the variability in the structures of social care networks, focusing on how the diverse needs of community members and the array of providers influence these structures. We posit that the architecture of these networks may hold the key to discerning patterns in community health and social outcomes. Our study examines the resilience of social care networks, defining

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Fernandez, Jasmine, Michaela Bonnett, Teri Garstka, and Meaghan Kennedy. Exploring Social Care Network Structures. Orange Sparkle Ball, 2024. http://dx.doi.org/10.61152/hdnz4028.

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McCulloh, Ian A., and Kathleen M. Carley. Social Network Change Detection. Defense Technical Information Center, 2008. http://dx.doi.org/10.21236/ada487504.

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Casasbuenas, Guillermo. Colombia: Solidarity Social Network. Inter-American Development Bank, 2001. http://dx.doi.org/10.18235/0012249.

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Over the last decades, social policy has been conceived from a sectorial perspective. This means that social policy responds more to government's organizational activities than to people's necessities; as if social problems could be approached from a unilateral perspective; in the same way that national, provincial or municipal budgets are allocated by "sectors".

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Bonnett, Michaela, Chimdi Ezeigwe, Meaghan Kennedy, and Teri Garstka. Using Social Network Analysis to Link Community Health and Network Strength. Orange Sparkle Ball, 2023. http://dx.doi.org/10.61152/scsf6662.

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Social network analysis (SNA) is a technique used to analyze social networks, whether it be composed of people, organizations, physical locations, or objects. It is being increasingly applied across a variety of sectors to gain insight into patterns of behavior and connectivity, the flow of information and behaviors, and to track and predict the effectiveness of interventions or programs. A key area associated with network strength using SNA is the health and wellness of individuals and communities. Both network strength and health and wellness are measured in many ways, which can obfuscate th

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Nentwich, Michael, ed. Potential and Impacts of Cloud Computing Services and Social Network Websites: Annex - Social Network Websites. Self, 2014. http://dx.doi.org/10.1553/ita-pb-a65-8.

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Johnson, Eric M., and Robert Chew. Social Network Analysis Methods for International Development. RTI Press, 2021. http://dx.doi.org/10.3768/rtipress.2021.rb.0026.2105.

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Social Network Analysis (SNA) is a promising yet underutilized tool in the international development field. SNA entails collecting and analyzing data to characterize and visualize social networks, where nodes represent network members and edges connecting nodes represent relationships or exchanges among them. SNA can help both researchers and practitioners understand the social, political, and economic relational dynamics at the heart of international development programming. It can inform program design, monitoring, and evaluation to answer questions related to where people get information; w

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McCulloh, Ian, Kathleen Carley, and Matthew Webb. Social Network Monitoring of Al-Qaeda. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada488339.

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Schmidt, Teresa. Statistical Analysis of Social Network Change. Portland State University Library, 2019. http://dx.doi.org/10.15760/etd.7288.

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