Identifying Influential Nodes in Online Social Networks Using Principal Component Centrality

Identifying the most influential nodes in social networks is a key problem in social network analysis. However, without a strict definition of centrality the notion of what constitutes a central node in a network changes with application and the type of commodity flowing through a network. In this paper we identify social hubs, nodes at the center of influential neighborhoods, in massive online social networks using principal component centrality (PCC). We compare PCC with eigenvector centrality´s (EVC), the de facto measure of node influence by virtue of their position in a network. We demonstrate PCC´s performance by processing a friendship graph of 70, 000 users of Google´s Orkut social networking service and a gaming graph of 143, 020 users obtained from users of Facebook´s ´Fighters Club´ application.