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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• 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
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• 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: https://www.flickr.com/photos/7855449@N02/2779601063
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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. LIPARI23/07/2014
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• 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: http://modcult.org/image/1976
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• 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.
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• 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
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• 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
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• Social semantic
Content based: e.g. Football fans
Project based: e.g. activists
Relationship based: e.g. friendship, brotherhood
https://www.flickr.com/photos/paulisson_miura/14265444730/
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• Place
Physical: e.g. neighbourood
Digital: e.g. social network connections
Blurred: e.g. earthquake tweets
https://www.flickr.com/photos/sierragoddess/5435989568/
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• 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)
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• 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”
http://www.chinaz.com/web/2012/1224/286875_2.shtml
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• 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”
http://journals.aps.org/prl/abstract/10.1103/PhysRevLett.94.160202
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• 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.
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• 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. LIPARI23/07/2014
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• 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
http://www.sociologiadeimediadigitali.it
Facebook fanpage
http://www.facebook.com/sociologiadeimedi
adigitali
Twitter
http://twitter.com/mediadigitali