Community-Driven Social Influence Analysis and Applications

Nowadays, people conduct a lot of activities with their online social networks. With the large amount of social data available, quantitative analysis of social influence becomes feasible. In this PhD project, we aim to study users’ social influence at the community level, mainly because users in social networks are naturally organized in communities and communities play fundamental roles in understanding social behaviors and social phenomenons. Through experiments with a location-based social networks dataset, we start by demonstrating communities’ influence on users’ mobility, and then we focus on the influence of leaders in the communities. As a next step, we intend to detect users that act as structural hole spanners and analyze their social influence across different communities. Based on these studies, we plan to propose a unified approach to quantify users’ social influence and investigate its applications, for example, in social interaction and behavior analysis.