Xu Changsheng

Overlapped user-based cross-network analysis: Exploring variety in big social media data

Social media contributes much to big data. Among the 4V characteristics of big data, this article focuses on investigating the variety in big social media data. Social media variety mainly concerns with the heterogeneous user behaviors in differenet social media networks. Understanding into social emdia variety plays important roles in insightful social media analysis and comprehensive social media applications. Social meida is typically generated from user and desinged for user services. We propose to explore social media variety by investigating the overlapped users between different social media networks. Two problems are discussed: (1) cross-network user modeling, where the scattered user behaviors are integrated for complete user modeling and personalized service development; (2) heterogeneous knowledge association, where the overlapped users serve as bridge to mine the cross-network knowledge association and applied in social media collaborative applications.