Data mining for social network analysis

Abstract

A social network is defined as a social structure of individuals, who are related (directly or indirectly to each other) based on a common relation of interest, e.g. friendship, trust, etc. Social network analysis is the study of social networks to understand their structure and behavior. Social network analysis has gained prominence due to its use in different applications - from product marketing (e.g. viral marketing) to search engines and organizational dynamics (e.g. management). Recently there has been a rapid increase in interest regarding social network analysis in the data mining community. The basic motivation is the demand to exploit knowledge from copious amounts of data collected, pertaining to social behavior of users in online environments. A prime example of this are the research efforts dedicated towards the Enron email dataset. Data mining based techniques are proving to be useful for analysis of social network data, especially for large datasets that cannot be handled by traditional methods. This talk will provide an up-to-date introduction to the increasingly important field of data mining in social network analysis, and a brief overview of research directions in this field. We first provide an introduction to social network analysis and then briefly survey the research in this field. Next, an overview of emerging research in data mining for social network analysis is presented. Finally, we will present our own work in two areas: (i) data mining for socio-cognitive analysis of email networks, and (ii) data mining on logs from massively multi-player online (MMO) games to understand social and group dynamics amongst players.