Using Interest Graphs to Predict Rich-Media Diffusion in Content-Based Online Social Networks

Abstract

Rich-media, pictures, and videos, are becoming an increasingly important aspect of online social networks. Unlike social networks, where users are connected primarily because of being friends, peers, or co-workers, content-based networks build connections between individuals founded on a shared interest in rich-media content. In this study, “interest-graphs” comprised of these content-based connections were examined. As shown, interest graph analysis provides important advantages over traditional social network analysis to identify valuable network members and predicting rich-media diffusion.

Keywords:

• business intelligence
• content-based network
• interest graphs
• social graphs
• social network analysis
• visual word of mouth

Additional information

Notes on contributors

E. Mitchell Church

E. Mitchell Church is an assistant professor of Information Systems in the E. Craig Wall Sr. College of Business Administration at Coastal Carolina University in Conway, SC. His research interests include online consumer behavior and the economic value of social media information. He has been published research in the Journal of Electronic Commerce Research and proceedings of national and international including the Americas Conference for Information Systems (AMCIS), the International Conference for Information Systems (ICIS), the Conference on Information Systems and Technology (CIST) and the Global Information Technology Management Association (GITMA). His teaching interests include the Management of Information Systems and Information Systems Project Management.

Lakshmi S. Iyer

Lakshmi S. Iyer is an associate professor and director of graduate programs in the Information Systems and Supply Chain Management Department at the University of North Carolina at Greensboro. Her research interests are in the area of BI, knowledge management, emerging technologies and its organizational impact, and social inclusion in computing. Her research work has been published in Communications of the AIS, Journal of Association for Information Systems, European Journal of Information Systems, Communications of the ACM, Decision Support Systems, eService Journal, Journal of Electronic Commerce Research, International Journal of Business Intelligence Research, Information Systems Management, and others.

Xia Zhao

Xia Zhao is an associate professor of Information Systems at the Bryan School of Business and Economics, The University of North Carolina at Greensboro. She received her PhD degree in management science and information systems from The University of Texas at Austin. She has published papers in Journal of Management Information Systems, Production and Operations Management, Decision Support Systems, Information Systems Frontier, IEEE Computer, International Journal of Electronic Commerce, and many conference proceedings. She has recently won the Bryan School Junior Faculty Research Excellence Award and the Emerald Citation of Excellence Award. She is a senior editor of Decision Support Systems.