Mining Social Profiles in Temporal Networks
Abstract
The number and types of relationship that members of a social network establish suggest the profile that each individual develops over time. In this paper, we propose a mining method capable of identifying and recovering social profiles from topological aspects in temporal networks. The application of this method allows the identification of persistent profiles and explicit patterns that suggest relationship models in social networks.
References
Burt, R. S. (1995). Structural Holes: The Social Structure of Competition. Harvard University Press, Cambridge.
Cohen, E., Delling, D., Pajor, T., and Werneck, R. F. (2014). Computing classic closeness centrality, at scale. In Proceedings of the Second ACM Conference on Online Social Networks, pages 37–50, Dublin, Ireland.
David, E., Jon, K., Easley, D., and Kleinberg, J. (2010). Networks, Crowds, and Markets: Reasoning About a Highly Connected World. Cambridge University Press, New York, NY, USA.
Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6):1360–1380.
Leão, J. C., Brandão, M. A., de Melo, P. O. V., and Laender, A. H. F. (2017). Classificação de relações sociais para melhorar a detecção de comunidades. In Proceedings of the VI Brazilian Workshop on Social Network Analysis and Mining, São Paulo, SP, Brazil.
Lin, N. (1999). Building a network theory of social capital. Connections, 22(1):28–51.
Podolny, J. M. and Baron, J. N. (1997). Resources and relationships: Social networks and mobility in the workplace. American Sociological Review, 62:673–693.
Vaz de Melo, P. O. S., Viana, A. C., Fiore, M., Jaffrès-Runser, K., Mouël, F. L., Loureiro, A. A. F., Addepalli, L., and Guangshuo, C. (2015). RECAST: Telling Apart Social and Random Relationships in Dynamic Networks. Performance Evaluation, 87:19–36.
