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Artykuły w czasopismach na temat „Social network”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 25 lipca 2025

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1

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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Treese, Win. "Social network?" netWorker 12, no. 1 (2008): 13–15. http://dx.doi.org/10.1145/1346942.1346946.

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Bongomin, George Okello Candiya, John C. Munene, Joseph Mpeera Ntayi, and Charles Akol Malinga. "Social network." African Journal of Economic and Management Studies 9, no. 3 (2018): 388–406. http://dx.doi.org/10.1108/ajems-07-2017-0157.

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Purpose The purpose of this paper is to test for the predictive power of each of the dimensions of social network in explaining financial inclusion of the poor in rural Uganda. Design/methodology/approach The study employed a cross-sectional research design and data were collected from a total of 400 poor households located in Northern, Eastern, Central and Western Uganda. The authors adopted ordinary least square hierarchical regression analysis to test for the predictive power of each of the dimensions of social network in explaining financial inclusion of the poor in rural Uganda. The effec

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Bolster, Mary. "Social Network." Brain & Life 16, no. 5 (2020): 38. http://dx.doi.org/10.1097/01.nnn.0000719040.69363.cd.

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Williams, Ruth, and Andrea Shaw. "Social network." Nursing Management 22, no. 6 (2015): 17. http://dx.doi.org/10.7748/nm.22.6.17.s24.

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Kutz, Giorgio. "Social network." Giornale della L 12, no. 6 (2013): 47–50. http://dx.doi.org/10.1472/ser-art-ve.

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Quinn, Darren, Liming Chen, and Maurice Mulvenna. "Social Network Analysis." International Journal of Ambient Computing and Intelligence 4, no. 3 (2012): 46–58. http://dx.doi.org/10.4018/jaci.2012070104.

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Social Network Analysis is attracting growing attention as social networking sites and their enabled applications transform and impact society. This paper aims to provide a comprehensive review of social network analysis state of the art research and practice. In the paper the authors’ first examine social networking and the core concepts and ingredients of social network analysis. Secondly, they review the trend of social networking and related research. The authors’ then consider modelling motivations, discussing models in line with tie formation approaches, where connections between nodes a

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Abdul Rauf, Siti Hajar, Siti Hajar Abu Bakar Ah, and Adi Fahrudin. "Social Change PostCOVID-19 in Malaysia: The Density of Social Network." Asian Social Work Journal 5, no. 2 (2020): 1–5. http://dx.doi.org/10.47405/aswj.v5i2.136.

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The COVID-19 pandemic is a global health problem that has given the greatest challenge for humanity today. This paper discusses the social changes that have taken place on social network density after COVID-19 hit the world. The social network density discussed is based on Social Network Theory according to the current situation that has hit Malaysia. The methods used are based on document analysis and case analysis from official documents issued by the government. The analysis revealed that the COVID-19 pandemic has had a devastating impact on human health, social and economic. However, seen

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Nasution, Mahyuddin K. M., Rahmad Syah, and Marischa Elveny. "Social Network Analysis: Towards Complexity Problem." Webology 18, no. 2 (2021): 449–61. http://dx.doi.org/10.14704/web/v18i2/web18332.

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Social network analysis is a advances from field of social networks. The structuring of social actors, with data models and involving intelligence abstracted in mathematics, and without analysis it will not present the function of social networks. However, graph theory inherits process and computational procedures for social network analysis, and it proves that social network analysis is mathematical and computational dependent on the degree of nodes in the graph or the degree of social actors in social networks. Of course, the process of acquiring social networks bequeathed the same complexit

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19

van Ijzendoorn, Marinus H. "Attachment in Social Networks: Toward an Evolutionary Social Network Model." Human Development 48, no. 1-2 (2005): 85–88. http://dx.doi.org/10.1159/000083218.

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Gemici, Kurtuluş, and Anthony Vashevko. "Visualizing Hierarchical Social Networks." Socius: Sociological Research for a Dynamic World 4 (January 1, 2018): 237802311877298. http://dx.doi.org/10.1177/2378023118772982.

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The authors propose a novel technique for the visualization of networks that contain a hierarchical structure: networks in which certain nodes and groups of nodes can be classified through a relation of precedence. Networks with a hierarchical structure frequently arise in sociology and various other disciplines, but the existing methods for visualizing such networks leave much to be desired. The method developed in this work builds on the tradition of visualization in social network analysis; it aims to simultaneously represent the positions of different nodes and the relationships between gr

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Đuričanin, Jasminka, Marko Gašić, Jelena Veličković, and Nebojša Pavlović. "Advertising on Facebook social network." Bizinfo Blace 12, no. 2 (2021): 171–81. http://dx.doi.org/10.5937/bizinfo2102171d.

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The exponential growth of users on social networks around the world has led companies to explore effective ways of their presence on social networks. Accordingly, the trend of advertising as one of the most important forms of communication mix has changed and now companies are mainly focused on advertising on social networks. There are many social networks that companies can use for advertising, however, this paper points to the importance of advertising through the social network Facebook, given the fact that Facebook is the largest and most popular social network in the world and is the perf

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Machuco Rosa, António. "Mimesis, network theory and digital social networks." Xiphias Gladius Revista interdisciplinar de Teoría Mimética, no. 1 (December 19, 2018): 93–111. http://dx.doi.org/10.32466/eufv-xg.2018.1.387.93-111.

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We analyse the formal theory of networks and the new digital media from the perspective of mimetic theory. It is emphasised that the spatial form of the new media is characterised by distribution functions that are power laws. We show that this spatial form can be derived from the presence of mimetic desire in digital social networks. Finally, we show that network theory allows the representation of the scapegoat mechanism as it was analysed by René Girard.

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Davel, Ronel, Adeline S. A. Du Toit, and Martie M. Mearns. "Understanding Knowledge Networks Through Social Network Analysis." International Journal of Knowledge Management 13, no. 2 (2017): 1–17. http://dx.doi.org/10.4018/ijkm.2017040101.

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Social network analysis (SNA) is being increasingly deployed as an instrument to plot knowledge and expertise as well as to confirm the character of connections in informal networks within organisations. This study investigated how the integration of networking into KM can produce significant advantages for organisations. The aim of the research was to examine how the interactions between SNA, Communities of Practice (CoPs) and knowledge maps could potentially influence knowledge networks. The researchers endeavour to illustrate via this question that cultivating synergies between SNA, CoPs an

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Liu, Guanfeng, Yan Wang, and Mehmet Orgun. "Social Context-Aware Trust Network Discovery in Complex Contextual Social Networks." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (2021): 101–7. http://dx.doi.org/10.1609/aaai.v26i1.8114.

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Trust is one of the most important factors for participants' decision-making in Online Social Networks (OSNs). The trust network from a source to a target without any prior interaction contains some important intermediate participants, the trust relations between the participants, and the social context, each of which has an important influence on trust evaluation. Thus, before performing any trust evaluation, the contextual trust network from a given source to a target needs to be extracted first, where constraints on the social context should also be considered to guarantee the quality of ex

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Cadima, Rita, Carlos Ferreira, Josep Monguet, Jordi Ojeda, and Joaquin Fernandez. "Promoting social network awareness: A social network monitoring system." Computers & Education 54, no. 4 (2010): 1233–40. http://dx.doi.org/10.1016/j.compedu.2009.11.009.

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Del Fresno García, Miguel. "Connecting the Disconnected: Social Work and Social Network Analysis. A Methodological Approach to Identifying Network Peer Leaders." Arbor 191, no. 771 (2015): a209. http://dx.doi.org/10.3989/arbor.2015.771n1011.

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Mahmudova, S. "SOCIAL NETWORKING SERVICES." Slovak international scientific journal, no. 83 (May 14, 2024): 24–25. https://doi.org/10.5281/zenodo.11188937.

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In the article, the services of Internet-media and social networks, this potential world trade, implementation of network monitoring, as well as production in the field of monitoring Internet-media resources, etc. investigated in studies. Nowadays, everyone can benefit from social networks. It can be network usage or otherwise oriented. Shab provides the abundance and availability of information, making the learning process more optimal and comfortable. Over the past 10 years, online social networks have become integral parts.

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Schmälzle, Ralf, Matthew Brook O’Donnell, Javier O. Garcia, et al. "Brain connectivity dynamics during social interaction reflect social network structure." Proceedings of the National Academy of Sciences 114, no. 20 (2017): 5153–58. http://dx.doi.org/10.1073/pnas.1616130114.

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Social ties are crucial for humans. Disruption of ties through social exclusion has a marked effect on our thoughts and feelings; however, such effects can be tempered by broader social network resources. Here, we use fMRI data acquired from 80 male adolescents to investigate how social exclusion modulates functional connectivity within and across brain networks involved in social pain and understanding the mental states of others (i.e., mentalizing). Furthermore, using objectively logged friendship network data, we examine how individual variability in brain reactivity to social exclusion rel

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Claybaugh, Craig C., and Peter Haried. "Professional Social Network Site Participation." International Journal of Virtual Communities and Social Networking 4, no. 4 (2012): 19–32. http://dx.doi.org/10.4018/jvcsn.2012100102.

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Online professional social networks have become a noteworthy tool to help professionals create, strengthen, and maintain valuable business connections. However, the question remains as to who is actually using online professional social networks and how the diffusion of the social network has occurred. Looking at diffusion and usage through innovation diffusion theory, critical mass and a network effects lens, this paper seeks to examine the diffusion of an online professional social network (LinkedIn) for a specific population of university business schools. Using longitudinal analysis (2008

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Niese, Bethany, and Sharath Sasidharan. "Getting Social." International Journal of Knowledge Management 18, no. 1 (2022): 1–23. http://dx.doi.org/10.4018/ijkm.313956.

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Knowledge acquired by end users through their social networks facilitates optimal use of a newly implemented enterprise system. Existing research has conceptualized end users as being the only actors within such networks. Knowledge ties between actors have been treated as unidimensional. The actor-network theory emphasizes the role of all actors in influencing networking outcomes; hence, this study proposes an expanded multimodal social network that includes four institutionally mandated knowledge actors: the technology champions, the help desk, the service desk, and the shared inbox. Knowledg

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AYDIN, Nursen. "Social Network Analysis: Literature Review." AJIT-e Online Academic Journal of Information Technology 9, no. 34 (2018): 73–80. http://dx.doi.org/10.5824/1309-1581.2018.4.005.x.

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In this article, social network analysis SNA is defined and historical development process is explained. A comprehensive literature search has been conducted for this purpose. SAA is a powerful method that centralizes individuals and their relations, in that the effect of the individual on the social network can be uncovered and the network of individual groups can be evaluated holistically. SNA shows the structural gaps and social capital in institutions, and focuses managers' attention on critical informal networks. Evaluating strategically important networks within an organization, make "in

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Lundberg, Heléne, and Christina Öberg. "A network of networks: knowledge development across network boundaries." Journal of Business & Industrial Marketing 40, no. 13 (2025): 77–86. https://doi.org/10.1108/jbim-07-2024-0502.

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Purpose The purpose of this paper is to examine knowledge development across network boundaries. Design/methodology/approach The empirical part of this paper is based on a longitudinal case study of a Swedish regional strategic network (RSN) in a sparely populated area. Data was collected through interviews, websites and social media. The case focuses on the creation of sub-networks designed to improve collaboration among different experts. The paper analyses how knowledge evolved across these sub-networks, the RSN and social and business networks. Findings The case study demonstrates how RSN

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Yang, Hong Mei, Chun Ying Zhang, Rui Tao Liang, and Fang Tian. "Set Pair Social Network Analysis Model." Applied Mechanics and Materials 50-51 (February 2011): 63–67. http://dx.doi.org/10.4028/www.scientific.net/amm.50-51.63.

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Through the study on social network information, this paper explore that there exists the certain and uncertain phenomena in the process of finding the relationship between individuals by using social networks, and the social networks are constantly changing. In light of there are some uncertainty and dynamic problems for the network, this paper put forward the set pair social network analysis model and set pair social network analysis model and its properties.

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Ștefan, Vlăduţescu. "CoMMunicational Basis of Social Networks." CoMMunicational Basis of Social Networks 2, no. 8 (2013): 01–05. https://doi.org/10.5281/zenodo.3413036.

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The study is coordinated by the communication-oriented Social Network Analysis. First, it explores the communicational fundamentals of the social network. Then downgrade highlights the communicative power of social networks emerging establishment. Also it brings some clarification i) the essential elements and processes that occur in networks and ii) the structure of the network as a social system

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Roth, Adam R. "Informal Caregiving and Social Capital: A Social Network Perspective." Research on Aging 42, no. 9-10 (2020): 272–80. http://dx.doi.org/10.1177/0164027520912659.

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A large literature emphasizes the importance of social relationships during the caregiving process. Yet these issues are seldom presented in a social network framework that examines the structure of caregivers’ personal networks. In this study, I examine how older caregivers experience changes in personal network structure. Using two waves from the National Social Life, Health, and Aging Project, I investigate whether caregivers are more or less likely to exhibit bridging or bonding capital potential compared to noncaregivers. I find that older adults transitioning into caregiving are more lik

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HARA, Shinji. "Social Network and Social Space." Geographical Review of Japa,. Ser. A, Chirigaku Hyoron 67, no. 10 (1994): 701–22. http://dx.doi.org/10.4157/grj1984a.67.10_701.

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Jalali, Zeinab S., Alireza Rezvanian, and Mohammad Reza Meybodi. "Social network sampling using spanning trees." International Journal of Modern Physics C 27, no. 05 (2016): 1650052. http://dx.doi.org/10.1142/s0129183116500522.

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Due to the large scales and limitations in accessing most online social networks, it is hard or infeasible to directly access them in a reasonable amount of time for studying and analysis. Hence, network sampling has emerged as a suitable technique to study and analyze real networks. The main goal of sampling online social networks is constructing a small scale sampled network which preserves the most important properties of the original network. In this paper, we propose two sampling algorithms for sampling online social networks using spanning trees. The first proposed sampling algorithm fin

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BURT, RONALD S. "Social network and temporal discounting." Network Science 5, no. 4 (2017): 411–40. http://dx.doi.org/10.1017/nws.2017.23.

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AbstractFor reasons of social influence and social logistics, people in closed networks are expected to experience time compression: The more closed a person's network, the steeper the person's discount function, and the more narrow the expected time horizon within which the person deliberates events and behavior. Consistent with the hypothesis, data on managers at the top of three organizations show network closure associated with a social life compressed into daily contact with colleagues. Further, language in closed networks is predominantly about current activities, ignoring the future. Fu

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Westaby, James D., and Adam K. Parr. "Network Goal Analysis of Social and Organizational Systems: Testing Dynamic Network Theory in Complex Social Networks." Journal of Applied Behavioral Science 56, no. 1 (2019): 107–29. http://dx.doi.org/10.1177/0021886319881496.

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Grounded in dynamic network theory, this study examined network goal analysis (NGA) to understand complex systems. NGA provides new insights by inserting goal nodes into social networks. Goal nodes can also represent missions, objectives, or desires, thus having wide applicability. The theory ties social networks to goal nodes through a parsimonious set of social network role linkages, such as independent goal striving, system supporting, feedback, goal preventing, supportive resisting, and system negating (i.e., those who are upset with others in the pursuit). Moreover, we extend the theory’s

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Smith, Edward Bishop, Raina A. Brands, Matthew E. Brashears, and Adam M. Kleinbaum. "Social Networks and Cognition." Annual Review of Sociology 46, no. 1 (2020): 159–74. http://dx.doi.org/10.1146/annurev-soc-121919-054736.

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Social network analysis, now often thought of simply as network science, has penetrated nearly every scientific and many scholarly fields and has become an indispensable resource. Yet, social networks are special by virtue of being specifically social, and our growing understanding of the brain is affecting our understanding of how social networks form, mature, and are exploited by their members. We discuss the expanding research on how the brain manages social information, how this information is heuristically processed, and how network cognitions are affected by situation and circumstance. I

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KC, Birendra, Duarte B. Morais, M. Nils Peterson, Erin Seekamp, and Jordan W. Smith. "Social network analysis of wildlife tourism microentrepreneurial network." Tourism and Hospitality Research 19, no. 2 (2017): 158–69. http://dx.doi.org/10.1177/1467358417715679.

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Social networks are an important element of entrepreneurship. Entrepreneurs rely on social networks to access ideas, information, and resources to facilitate their entrepreneurial process. Strong and weak ties influence the entrepreneurial process in unique ways. This study utilized social network analysis approach to examine wildlife tourism microentrepreneurship through in-person structured interviews with 37 microentrepreneurs from North Carolina’s Pamlico Sound Region. Specifically, this study examined the extent of network ties, the type of support received from those network ties, and th

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Leinart, James Andrew, and Richard Deckro. "Revealing Bridges in Social Networks." Military Operations Research 29, no. 1 (2024): 75–94. http://dx.doi.org/10.5711/1082598329175.

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Social groups and networks are ubiquitous, and each network member typically has a role or roles in associated interactions. One such member identified in social network literature is a bridge, which connects two or more groups, and is an element of only one of the groups; inferred from literature is the notion that bridges play a key role in networks. At different times and for various reasons, network and group components may be unrevealed. An example is a terrorist network; the terrorists may know who comprises their network, but a military or security organization that is attempting to dis

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Lumino, Rosaria, Giancarlo Ragozini, and Maria Prosperina Vitale. "Investigating social support patterns of single mothers from a social network perspective." International Review of Social Research 6, no. 4 (2016): 182–94. http://dx.doi.org/10.1515/irsr-2016-0021.

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AbstractIn the present study, we discuss how social network analysis approach can be fruitful exploited to study social support within family studies. An ego-centred network approach is adopted within a case study about social support networks of low income single mothers living in a city of southern Italy. We address three main issues. First, we aim to describe and explore the structure of social relationships that single mothers activate in order to obtain different kind of supports. Second, we investigate the main factors that affect the amount and variety of resources embedded in the singl

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Litwin, Howard. "Social Predictors of Physical Activity in Later Life: The Contribution of Social-Network Type." Journal of Aging and Physical Activity 11, no. 3 (2003): 389–406. http://dx.doi.org/10.1123/japa.11.3.389.

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The purpose of this study was to examine the association of social-network type and physical activity in an elderly population. The analysis was based on secondary analysis of a sample of Israeli retirees (N= 1,493). Five network types were considered: diverse, friends, neighbors, family, and restricted networks. Sociodemographic and health variables were addressed as control variables. A dichotomous physical activity measure was regressed in a hierarchical logistic procedure on the control and network-type variables. The multivariate results showed that respondents in diverse networks had the

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Maiz, Ander, Nieves Arranz, and Juan Carlos Fdez. de Arroyabe. "Factors affecting social interaction on social network sites: the Facebook case." Journal of Enterprise Information Management 29, no. 5 (2016): 630–49. http://dx.doi.org/10.1108/jeim-10-2014-0105.

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Purpose The purpose of this paper is to focus on understanding the factors which affect the social interaction in the case of Facebook. Many authors point out the great potential of these networks for social interaction and as conduits of information. However, studies show that the topology of the network is disconnected, consisting of small sub-networks that make Facebook unsuitable for disseminating information. This situation has created the need to introduce exogenous factors, aimed at boosting and providing cohesion to the network structure. In this context, the authors test the following

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Smailovic, Vanja, Vedran Podobnik, and Ignac Lovrek. "A Methodology for Evaluating Algorithms That Calculate Social Influence in Complex Social Networks." Complexity 2018 (August 8, 2018): 1–20. http://dx.doi.org/10.1155/2018/1084795.

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Online social networks are complex systems often involving millions or even billions of users. Understanding the dynamics of a social network requires analysing characteristics of the network (in its entirety) and the users (as individuals). This paper focuses on calculating user’s social influence, which depends on (i) the user’s positioning in the social network and (ii) interactions between the user and all other users in the social network. Given that data on all users in the social network is required to calculate social influence, something not applicable for today’s social networks, alt

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Deng, Huan, Cailin Abouzeid, Lauren Shepler, et al. "802 Characteristics of Personal Social Network Associated with Social Participation Outcomes After Burn Injury." Journal of Burn Care & Research 46, Supplement_1 (2025): S256. https://doi.org/10.1093/jbcr/iraf019.333.

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Abstract Introduction A personal social network is the set of family, friends and acquaintances surrounding an individual and their interpersonal connections. Personal social networks have shown close associations with an individual’s physical health, mental wellbeing, and social outcomes. People with burn injury commonly experience social participation challenges for years. The association between recovery outcomes and personal social network is unclear. Thus, this study aims to examine the relationship between personal social network characteristics and social participation outcomes after bu

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Gong, Yuhui, and Qian Yu. "Evolution of Conformity Dynamics in Complex Social Networks." Symmetry 11, no. 3 (2019): 299. http://dx.doi.org/10.3390/sym11030299.

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Conformity is a common phenomenon among people in social networks. In this paper, we focus on customers’ conformity behaviors in a symmetry market where customers are located in a social network. We establish a conformity model and analyze it in ring network, random network, small-world network, and scale-free network. Our simulations shown that topology structure, network size, and initial market share have significant effects on the evolution of customers’ conformity behaviors. The market will likely converge to a monopoly state in small-world networks but will form a duopoly market in scale

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Li, Ning, Qian Huang, Xiaoyu Ge, et al. "A Review of the Research Progress of Social Network Structure." Complexity 2021 (January 7, 2021): 1–14. http://dx.doi.org/10.1155/2021/6692210.

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Social network theory is an important paradigm of social structure research, which has been widely used in various fields of research. This paper reviews the development process and the latest progress of social network theory research and analyzes the research application of social network. In order to reveal the deep social structure, this paper analyzes the structure of social networks from three levels: microlevel, mesolevel, and macrolevel and reveals the origin, development, perfection, and latest achievements of complex network models. The regular graph model, P1 model, P2 model, expone

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Li, Ning, Qian Huang, Xiaoyu Ge, et al. "A Review of the Research Progress of Social Network Structure." Complexity 2021 (January 7, 2021): 1–14. http://dx.doi.org/10.1155/2021/6692210.

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Social network theory is an important paradigm of social structure research, which has been widely used in various fields of research. This paper reviews the development process and the latest progress of social network theory research and analyzes the research application of social network. In order to reveal the deep social structure, this paper analyzes the structure of social networks from three levels: microlevel, mesolevel, and macrolevel and reveals the origin, development, perfection, and latest achievements of complex network models. The regular graph model, P1 model, P2 model, expone

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