Exploiting Personal and Community Context in Mobile Social Networks

Abstract

Mobile social networks (MSNs) are believed to be more user-friendly and intelligent than online social networks. In this chapter, we first extend the definition of mobile social networks by classifying MSNs into four categories, and define two important terms, e.g., personal context and community context in the emerging field of mobile social networks. We then present the context model and the related taxonomy of personal context and community context. We further divide the life cycle of MSNs into four phases --- discovery, connection, interaction, and management --- and elaborate how personal context and community context facilitates the process in each phase. Three major data sources for deriving personal and community context in MSNs are identified, e.g., sensor-rich mobile and wearable devices, Internet applications and Web services, and static infrastructure. Leveraging the three data sources, techniques ranging from data representation, data cleansing, and data anonymization to clustering techniques and inference techniques are presented for inferring personal and community context. Finally, future research directions and challenges are identified, in order to shed light on next-generation MSN development from the context-aware perspectives.