Segregation Discovery in a Social Network of Companies
We introduce a framework for a data-driven analysis of segregation of minority groups in social networks, and challenge it on a complex scenario. The framework builds on quantitative measures of segregation, called segregation indexes, proposed in the social science literature. The segregation discovery problem consists of searching sub-graphs and sub-groups for which a reference segregation index is above a minimum threshold. A search algorithm is devised that solves the segregation problem. The framework is challenged on the analysis of segregation of social groups in the boards of directors of the real and large network of Italian companies connected through shared directors.
KeywordsMinority Group Information Index Italian Company Giant Component Dissimilarity Index
- 5.Bothorel, C., Cruz, J.D., Magnani, M., Micenková, B.: Clustering attributed graphs: models, measures and methods. Network Science FirstView, 1–37 (2015)Google Scholar
- 6.Das, S., Kramer, A.D.I.: Self-censorship on Facebook. In: Proceedings of the International Conference on Weblogs and Social Media (ICWSM 2013). The AAAI Press (2013)Google Scholar
- 7.Fischer, E.: Distribution of race and ethnicity in US major cities (2011) (published on line at http://www.flickr.com/photos/walkingsf under Creative Commons licence, CC BY-SA 2.0)
- 16.Pariser, E.: The Filter Bubble: What the Internet is Hiding from you. Penguin, UK (2011)Google Scholar
- 17.Pedreschi, D., Ruggieri, S., Turini, F.: A study of top-k measures for discrimination discovery. In: Proceedings of ACM International Symposium on Applied Computing (SAC 2012), pp. 126–131. ACM (2012)Google Scholar