Community detection from a computational social science perspective


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This is the talk I gave at the Lipari Summer School on Computational Social Science, 2014. Which are the sociological strategies to detect communities in social media? How we can define a community form a computational social science point of view?

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Community detection from a computational social science perspective

  2. 2. LIPARI23/07/2014 DAVIDEBENNATO
  3. 3. LIPARI23/07/2014 DAVIDEBENNATO
  5. 5. LIPARI23/07/2014 DAVIDEBENNATO • Ferdinand Tönnies: Gemeinschaft und Gesellschaft (1887)  Community: groupings based on feelings of togetherness and on mutual bonds  Society: groups that are sustained by it being instrumental for their members' individual aims and goals
  6. 6. LIPARI23/07/2014 DAVIDEBENNATO • Georg Simmel: Sociability (1908)  All the forms of association by which a mere sum of separate individuals are made into a “society” (Ritzer)  Social geometry: dyad (relation between two entities), triad (relation between three entities)  Circles: social structure surrounding people based on a special interest David Armano:
  7. 7. LIPARI23/07/2014 DAVIDEBENNATO
  8. 8. LIPARI23/07/2014 DAVIDEBENNATO I thus designate sociability as the play-form of sociation. Its relation to content- determined, concrete sociation is similar to that of the work of art to reality. [...] Sociability has no objective purpose, no content, no extrinsic results, it entirely depends on the personalities among whom it occurs. Its aim is nothing but the success of the sociable moment and, at most, a memory of it. Hence the conditions and results of the process of sociability are exclusively the persons who find themselves at a social gathering. (G. Simmel, 1908) I thus designate sociability as the play-form of sociation. Its relation to content- determined, concrete sociation is similar to that of the work of art to reality. [...] Sociability has no objective purpose, no content, no extrinsic results, it entirely depends on the personalities among whom it occurs. Its aim is nothing but the success of the sociable moment and, at most, a memory of it. Hence the conditions and results of the process of sociability are exclusively the persons who find themselves at a social gathering. (G. Simmel, 1908)
  9. 9. LIPARI23/07/2014 DAVIDEBENNATO • Barry Wellman: Networked individualism (2002)  A community is a network of relationship  «in practice, societies and people’s lives are often mixtures of groups and networks» Mark Lombardi:
  10. 10. LIPARI23/07/2014 DAVIDEBENNATO
  11. 11. LIPARI23/07/2014 DAVIDEBENNATO • Little boxes (Wellman 2002) Pre-industrial social relationships were based on itinerant bands, agrarian villages, trading towns, and urban neighborhoods. People walked door-to-door to visit each other in spatially compact and densely-knit milieus. If most settlements or neighborhoods contained less than a thousand people, then almost everybody would know each other. Communities were bounded, so that most relationships happened within their gates rather than across them. Much interaction stayed within neighborhoods, even in big cities and trading towns. When people visited someone, most neighbors knew who was going to see whom and what their interaction was about. Contact was essentially between households, with the awareness, sanction and control of the settlement.
  12. 12. LIPARI23/07/2014 DAVIDEBENNATO • Glocalized networks (Wellman 2002) If “community” is defined socially rather than spatially, then it is clear that contemporary communities rarely are limited to neighborhoods. They are communities of shared interest rather than communities of shared kinship or locality. People usually obtain support, companionship, information and a sense of belonging from those who do not live within the same neighborhood or even within the same metropolitan area. Many people’s work involves contact with shifting sets of people in other units, workplaces, and even other organizations. People maintain these ties through phoning, emailing, writing, driving, railroading, transiting, and flying
  13. 13. LIPARI23/07/2014 DAVIDEBENNATO • Networked Individualism (Wellman 2002) We are now experiencing another transition, from place-to-place to person-to-person connectivity. Moving around with a mobile phone, pager, or wireless Internet makes people less dependent on place. Because connections are to people and not to places, the technology affords shifting of work and community ties from linking people-in-places to linking people wherever they are. It is I-alone that is reachable wherever I am: at a house, hotel, office, freeway or mall. The person has become the portal […] The shift to a personalized, wireless world affords networked individualism, with each person switching between ties and networks. People remain connected, but as individuals rather than being rooted in the home bases of work unit and household. Individuals switch rapidly between their social networks. Each person separately operates his networks to obtain information, collaboration, orders, support, sociability, and a sense of belonging
  15. 15. LIPARI23/07/2014 DAVIDEBENNATO • People  Little number  Large number
  16. 16. LIPARI23/07/2014 DAVIDEBENNATO • Relationship  Strong: stable, everyday  Weak: unstable, seldom
  17. 17. LIPARI23/07/2014 DAVIDEBENNATO • Social semantic  Content based: e.g. Football fans  Project based: e.g. activists  Relationship based: e.g. friendship, brotherhood
  18. 18. LIPARI23/07/2014 DAVIDEBENNATO • Time  Permanent: e.g. family ties  Temporary: e.g. media audience
  19. 19. LIPARI23/07/2014 DAVIDEBENNATO • Place  Physical: e.g. neighbourood  Digital: e.g. social network connections  Blurred: e.g. earthquake tweets
  21. 21. LIPARI23/07/2014 DAVIDEBENNATO • Concept: Modularity  “It’s a formalization of the idea that communities should contain many connection within and few outside of the group”(Jürgens 2014)
  22. 22. LIPARI23/07/2014 DAVIDEBENNATO • Concept: Clique  “A clique is a subset of points in which every possibile pair of points is directly connected by a line and the clique is not contained in any other clique” (Scott 2000)
  23. 23. LIPARI23/07/2014 DAVIDEBENNATO • Algorithm: Girvan and Newman (Jürgens 2014)  “It’s based on “betweenness centrality”: how many shortest paths across the network lead through one link”  “One by one the links through which the most short connections lead are removed”
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  25. 25. LIPARI23/07/2014 DAVIDEBENNATO • Algorithm: clique percolation (Jürgens 2014)  “Networks can be said to have choke points that separate two well connected areas from each other.”  “CP finds cliques where every node is connected to every other node and “moves” them across the network until they reach a choke point”  “As the algorithm increases the size of cliques fewer and fewer communities exist”
  26. 26. LIPARI23/07/2014 DAVIDEBENNATO
  28. 28. LIPARI23/07/2014 DAVIDEBENNATO Political blogosfere (Adamic, Glance 2005)
  29. 29. LIPARI23/07/2014 DAVIDEBENNATO
  30. 30. LIPARI23/07/2014 DAVIDEBENNATO
  31. 31. LIPARI23/07/2014 DAVIDEBENNATO
  32. 32. LIPARI23/07/2014 DAVIDEBENNATO Mapping Twitter Topic Networks (Pew Research Center 2014)
  33. 33. LIPARI23/07/2014 DAVIDEBENNATO Majoral candidates in Catania (Bennato, Miceli 2013 )
  34. 34. LIPARI23/07/2014 DAVIDEBENNATO Resignation Benedict XVI (Bennato, Miceli 2013 )
  35. 35. LIPARI23/07/2014 DAVIDEBENNATO Festival of Saint Agatha in Catania (Bennato, Miceli 2013 )
  36. 36. LIPARI23/07/2014 DAVIDEBENNATO • Mentionmapp  Research strategy: networking  Metrics: followers, hashtags
  37. 37. LIPARI23/07/2014 DAVIDEBENNATO • Analyzing relationship (SNA approach)  NodeXL:  Gephi:
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  39. 39. LIPARI23/07/2014 DAVIDEBENNATO • Bigliography  Adamic, L., Glance, N., 2005, The Political Blogosphere and the 2004 U.S. Election: Divided They Blog, LinkKDD '05 Proceedings of the 3rd international workshop on Link discovery, pp.36-43  Jürgens, P., 2014, Communities of Communication: Making Sense of the “Social” in social Media, in Bredl, K., Hünninger, J., Jensen, J. L., (Eds.), Methods for analyzing Social Media, Routledge, London, pp.45-62.  Scott, J., 2000, Social Network Analysis, Sage, London.  Wellman, B., 2002, Little Boxes, Glocalization, and Networked Individualism, in M. Tanabe, P. van den Besselaar, T. Ishida (Eds.), Digital Cities, Springer-Verlag, Berlin.  Welser H. T. , Smith M., Fisher D., Gleave E., 2008, Distilling digital traces: Computational social science approaches to Studying the Internet, in Fielding N., Lee M. L., Blank G., The SAGE Handbook of online research methods, SAGE, London, pp.116-140.
  40. 40. LIPARI23/07/2014 DAVIDEBENNATO • Davide Bennato is professor of Sociology of culture and communication and Sociology of digital media at the Department of Humanistic Sciences at the University of Catania. • He was professor for different italian universities: Roma “La Sapienza”, LUISS, Università di Siena, Università del Molise. • He is one of the founding members and vice- president (2005-08) of STS-Italia (Science and Technology Studies Italian Association). He is member of the board of Bench s.r.l., a University of Catania spin off in social and marketing researches. • His research topics are: technological cultures, digital content consumptions, social media interpersonal relationship. • His studies are based on computational social science, a computer based approach on social relationship and cultural modelling, using social analytics techniques. • Books: Le metafore del computer. La costruzione sociale dell’informatica (Meltemi, 2002) e Sociologia dei media digitali (Laterza, 2011). • Books chapters: 2014a, The Open Laboratory: Limits and Possibilities of Using Facebook, Twitter, and YouTube as a Research Data Source, (con F. Giglietto, L. Rossi, in Bredl et al, eds, Methods for analyzing Social media, Routledge, New York), 2014b, Smart City, Smart Data. L’uso dei dati alla ricerca di una città sostenibile, in “Lettera Internazionale”, n.118, pp. 40-43, 2014c, Etica dei Big data. Le conseguenze sociali della raccolta massiva di informazioni, in “Studi culturali”, n.1, pp.86-92, forthcoming, La dataveglianza di massa. Conseguenze etiche e relazionali delle scelte tecnologiche di Facebook, in Greco G., a cura, Pubbliche intimità. L’affettivo quotidiano nei siti di social network, Franco Angeli, Milano, pp.107-118.
  41. 41. LIPARI23/07/2014 DAVIDEBENNATO • Davide Bennato  Sociologia dei media digitali, Laterza, Roma-Bari, 2011 • Millions of people consult and interact with each other through the use of internet. Each in its own way, participate in the networking of news, but also to the transformation of these tools of communication and socialization. Blogs, wikis, social networks are - above all - tools of social relationship. The participative web then obliges a profound rethinking of the classical concepts of the sociology of communication. • Davide Bennato offers a detailed analysis of the different tools and platforms well known to the public, from Facebook to Youtube, and examines the ethical and social consequences of the use of new technologies. • The book on internet  website   Facebook fanpage  adigitali  Twitter 
  42. 42. LIPARI23/07/2014 DAVIDEBENNATO Socialmedia Skype davide.bennato Blog