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Social network analysis

This article is about the theoretical concept. For quantitative application to social media, see social media analytics. For social networking sites, see social networking service. For other uses, see Social network (disambiguation).

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A social network diagram displaying friendship ties among a set of Facebook users.

Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory.[1] It characterizes networked structures in terms of nodes (individual actors, people, or things within the network) and the ties, edges, or links (relationships or interactions) that connect them. Examples of social structures commonly visualized through social network analysis include social media networks,[2][3] meme spread,[4] information circulation,[5] friendship and acquaintance networks, peer learner networks,[6] business networks, knowledge networks,[7][8] difficult working relationships,[9] collaboration graphs, kinship, disease transmission, and sexual relationships.[10][11] These networks are often visualized through sociograms in which nodes are represented as points and ties are represented as lines. These visualizations provide a means of qualitatively assessing networks by varying the visual representation of their nodes and edges to reflect attributes of interest.[12]

Social network analysis has emerged as a key technique in modern sociology. It has also gained significant popularity in the following: anthropology, biology,[13] demography, communication studies,[3][14] economics, geography, history, information science, organizational studies,[7][9] physics,[15] political science,[16] public health,[17][8] social psychology, development studies, sociolinguistics, and computer science,[18] education and distance education research,[19] and is now commonly available as a consumer tool (see the list of SNA software).[20][21][22]

  1. ^ Otte, Evelien; Rousseau, Ronald (December 2002). "Social network analysis: a powerful strategy, also for the information sciences". Journal of Information Science. 28 (6): 441–453. doi:10.1177/016555150202800601. S2CID 17454166.
  2. ^ Grandjean, Martin (December 31, 2016). "A social network analysis of Twitter: Mapping the digital humanities community". Cogent Arts & Humanities. 3 (1). doi:10.1080/23311983.2016.1171458. S2CID 114999767.
  3. ^ a b Hagen, Loni; Keller, Thomas; Neely, Stephen; DePaula, Nic; Robert-Cooperman, Claudia (October 2018). "Crisis Communications in the Age of Social Media: A Network Analysis of Zika-Related Tweets". Social Science Computer Review. 36 (5): 523–541. doi:10.1177/0894439317721985. OCLC 7323548177. S2CID 67362137.
  4. ^ Nasrinpour, Hamid Reza; Friesen, Marcia R.; McLeod, Robert D. (November 22, 2016). "An Agent-Based Model of Message Propagation in the Facebook Electronic Social Network". arXiv:1611.07454 [cs.SI].
  5. ^ Grandjean, Martin (2022). "The Paris/Geneva Divide. A Network Analysis of the Archives of the International Committee on Intellectual Cooperation of the League of Nations" (PDF). Culture as Soft Power: Bridging Cultural Relations, Intellectual Cooperation, and Cultural Diplomacy: 65–98. doi:10.1515/9783110744552-004.
  6. ^ Paradowski, Michał B.; Jarynowski, Andrzej; Czopek, Karolina; Jelińska, Magdalena; et al. (2021). "Peer interactions and second language learning: The contributions of Social Network Analysis in Study Abroad vs At-Home environments". In Mitchell, Rosamond; Tyne, Henry (eds.). Language, Mobility and Study Abroad in the Contemporary European Context. New York: Routledge. pp. 99–116. doi:10.1017/S0261444820000580. ISBN 978-10-03087-95-3. S2CID 228863564.
  7. ^ a b Brennecke, Julia; Rank, Olaf (May 2017). "The firm's knowledge network and the transfer of advice among corporate inventors—A multilevel network study". Research Policy. 46 (4): 768–783. doi:10.1016/j.respol.2017.02.002.
  8. ^ a b Harris, Jenine K.; Luke, Douglas A.; Zuckerman, Rachael B.; Shelton, Sarah C. (June 2009). "Forty Years of Secondhand Smoke Research". American Journal of Preventive Medicine. 36 (6): 538–548. doi:10.1016/j.amepre.2009.01.039. OCLC 6980180781. PMID 19372026.
  9. ^ a b Cite error: The named reference Brennecke2019 was invoked but never defined (see the help page).
  10. ^ Pinheiro, Carlos A.R. (2011). Social Network Analysis in Telecommunications. John Wiley & Sons. p. 4. ISBN 978-1-118-01094-5.
  11. ^ D'Andrea, Alessia; et al. (2009). "An Overview of Methods for Virtual Social Network Analysis". In Abraham, Ajith (ed.). Computational Social Network Analysis: Trends, Tools and Research Advances. Springer. p. 8. ISBN 978-1-84882-228-3.
  12. ^ Grunspan, Daniel (January 23, 2014). "Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research". CBE: Life Sciences Education. 13 (2): 167–178. doi:10.1187/cbe.13-08-0162. PMC 4041496. PMID 26086650.
  13. ^ Tringali, Angela; Sherer, David L.; Cosgrove, Jillian; Bowman, Reed (February 10, 2020). "Life history stage explains behavior in a social network before and during the early breeding season in a cooperatively breeding bird". PeerJ. 8: e8302. doi:10.7717/peerj.8302. PMC 7020825. PMID 32095315.
  14. ^ Social network differences of chronotypes identified from mobile phone data. 2018. OCLC 1062367169.[page needed]
  15. ^ Gao, Min; Li, Zheng; Li, Ruichen; Cui, Chenhao; Chen, Xinyuan; Ye, Bodian; Li, Yupeng; Gu, Weiwei; Gong, Qingyuan; Wang, Xin; Chen, Yang (October 2023). "EasyGraph: A multifunctional, cross-platform, and effective library for interdisciplinary network analysis" (PDF). Patterns. 4 (10): 100839. doi:10.1016/j.patter.2023.100839. PMC 10591136. PMID 37876903.
  16. ^ Kim, Rakhyun E (November 26, 2020). "Is Global Governance Fragmented, Polycentric, or Complex? The State of the Art of the Network Approach". International Studies Review. 22 (4): 903–931. doi:10.1093/isr/viz052.
  17. ^ Harris, Jenine K.; Clements, Bruce (July 2007). "Using Social Network Analysis to Understand Missouri's System of Public Health Emergency Planners". Public Health Reports. 122 (4): 488–498. doi:10.1177/003335490712200410. OCLC 8062393936. PMC 1888499. PMID 17639652.
  18. ^ Ghanbarnejad, Fakhteh; Saha Roy, Rishiraj; Karimi, Fariba; Delvenne, Jean-Charles; Mitra, Bivas (2019). Dynamics On and Of Complex Networks III Machine Learning and Statistical Physics Approaches. Cham: Springer International Publishing : Imprint: Springer. ISBN 9783030146832. OCLC 1115074203.[page needed]
  19. ^ Bozkurt, Aras; Akgun-Ozbek, Ela; Yilmazel, Sibel; Erdogdu, Erdem; Ucar, Hasan; Guler, Emel; Sezgin, Sezan; Karadeniz, Abdulkadir; Sen-Ersoy, Nazife; Goksel-Canbek, Nil; Dincer, Gokhan Deniz; Ari, Suleyman; Aydin, Cengiz Hakan (January 20, 2015). "Trends in distance education research: A content analysis of journals 2009–2013". The International Review of Research in Open and Distributed Learning. 16 (1). doi:10.19173/irrodl.v16i1.1953. ISSN 1492-3831.
  20. ^ "Facebook friends mapped by Wolfram Alpha app". BBC News. September 24, 2012. Retrieved July 25, 2016.
  21. ^ Frederic Lardinois (August 30, 2012). "Wolfram Alpha Launches Personal Analytics Reports For Facebook". Tech Crunch. Retrieved July 25, 2016.
  22. ^ Ivaldi M.; Ferreri L.; Daolio F.; Giacobini M.; Tomassini M.; Rainoldi A. "We-Sport: from academy spin-off to data-base for complex network analysis; an innovative approach to a new technology". J Sports Med Phys Fitness. 51 (suppl. 1 to issue 3). hdl:2318/90491. The social network analysis was used to analyze properties of the network We-Sport.com allowing a deep interpretation and analysis of the level of aggregation phenomena in the specific context of sport and physical exercise.

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