European Journal of Social Behaviour
Published June 30, 2015 | Version v1
Journal article Open

Visualizations of personal social networks on Facebook and community structure: an exploratory study

Creators

  • 1. Department of Psychology, Panteion University of Social and Political Sciences.

Description

We studied the community structure pattern in the visualizations of ten personal social networks on Facebook at a single point in time. It seems to be a strong tendency towards community formation in online personal, social networks: somebody’s friends are usually also friends between them, forming subgroups of more densely connected nodes. Research on community structure in social networks usually focuses on the networks’ statistical properties. There is a need for qualitative studies bridging the gap between network topologies and their sociological implications. To this direction, visual representations of personal networks in social media could be a valuable source of
empirical data for qualitative interpretation. Most of the personal social networks’ visualizations in the present study are very highly clustered with densely-knit overlapping subgroups of friends and interconnected between them through wide bridges. This network topology pattern seems to be quite efficient, allowing for a fast spread and diffusion of information across the whole social network.

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References

  • Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: An open source software for exploring and manipulating networks. Presented at the International AAAI Conference on Weblogs and Social Media. Retrieved from http://www.aaai.org/ocs/index.php/ICWSM/09/paper/view/154
  • Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 10, 10008 (12 pp).
  • Calvino, I. (1974). Invisible Cities. USA: Harcourt Brace & Company.
  • Centola, D. (2015). The Social Origins of Networks and Diffusion. American Journal of Sociology, 120(5), 1295–1338. http://doi.org/10.1086/681275
  • Feldman, D. P. (2012). Chaos and Fractals: An Elementary Introduction. UK: Oxford University Press.
  • Ferrara, E. (2012a). A large-scale community structure analysis in Facebook. EPJ Data Science, 1(1), 1-30. doi:10.1140/epjds9
  • Ferrara, E. (2012b). Community structure discovery in Facebook. Int. J. of Social Network Mining, 2012 Vol.1, No.1, pp.67–90. 10.1504/IJSNM.2012.045106
  • Holquist, M. (2002). Dialogism: Bakhtin and His World. New York: Routledge.
  • Jacomy, M., Heymann, S., Venturini, T., & Bastian, M. (2012). ForceAtlas2, a continuous graph layout algorithm for handy network visualization. Retrieved from http://www.medialab.sciences- po.fr/publications/Jacomy_Heymann_Venturini-Force_Atlas2.pdf
  • Kauffman, S. (1996). At Home in the Universe: The Search for the Laws of Self- Organization and Complexity. USA: Oxford University Press.
  • Lambiotte, R., Delvenne, J. C., & Barahona, M. (2009). Laplacian dynamics and multiscale modular structure in networks. Arxiv preprint arXiv:0812.1770. Retrieved from http://arxiv.org/pdf/0812.1770v3.pdf
  • Milgram, S. (1967). The small world problem. Psychology today, 2(1), 60-67.
  • Mitchell, M. (2009). Complexity: A Guided Tour. USA: Oxford University Press.
  • Newman, M., Barabási, A. L., & Watts, D. J. (2006). The Structure and Dynamics of Networks. USA: Princeton University Press.
  • Nguyen, A. D., Senac, P., & Diaz, M. (2012). Understanding and modeling the small-world phenomenon in dynamic networks. In Proceedings of the 15th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems (pp. 377–384). Paphos, Cyprus: ACM.
  • Rieder, B. (2013). Studying Facebook via Data Extraction: The Netvizz Application. In Proceedings of the 5th Annual ACM Web Science Conference (pp. 346–355). Paris, France: ACM. http://doi.org/10.1145/2464464.2464475
  • Watts, D. (2004). Six Degrees: The New Science of Networks. UK: Random House.
  • Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of 'small-world' networks. Nature, 393(6684), 440-442. doi:10.1038/30918