Social Network Data Analytics

Charu C. Aggarwal obtained his B.Tech in Computer Science from IIT Kanpur in 1993 and Ph.D. from MIT in 1996. He has been a Research Staff Member at IBM since then, and has published over 140 papers in major conferences and journals in the database and data mining field. He has applied for or been granted over 75 US and International patents, and has thrice been designated Master Inventor at IBM for the commercial value of his patents. He has been granted 18 invention achievement awards by IBM for his patents. His work on real time stream analysis was recognized with the IBM Epispire award for environmental excellence in 2003, and the IBM Outstanding Technical Achievement award in 2010. His contributions to privacy technology were recognized with the IBM Outstanding Innovation Award in 2008. He has served on the program committee of most major data mining conferences, and was program vice-chairs for the WWW Conference, 2009, for the ICDM Conference and SIAM Data Mining Conference several times. He has also served as program chair for several workshops. He served as an associate editor of the IEEE Transactions on Data Engineering for two terms from 2004 to 2008. He is an associate editor of the ACM SIGKDD Explorations, an action editor of the Data Mining and Knowledge Discovery Journal, and an editorial board member of the Knowledge and Information Systems Journal. He is a fellow of the IEEE for contributions to knowledge discovery and data mining algorithms.

• An Introduction to Social Network Data Analytics.- Statistical Properties of Social Networks.- RandomWalks in Social Networks and their Applications: A Survey.- Community Discovery in Social Networks: Applications, Methods and Emerging Trends.- Node Classification in Social Networks.- Evolution in Social Networks: A Survey.- A Survey of Models and Algorithms for Social Influence Analysis.- A Survey of Algorithms and Systems for Expert Location in Social Networks.- A Survey of Link Prediction in Social Networks.- Privacy in Social Networks: A Survey.- Visualizing Social Networks.- Data Mining in Social Media.- Text Mining in Social Networks.- Integrating Sensors and Social Networks.- Multimedia Information Networks in Social Media.- An Overview of Social Tagging and Applications

From the reviews: "Provides a comprehensive compendium of the state of the art in social network data mining. ... a very interesting book for computer science researchers and practitioners who work in the area of data mining and want to learn the state of the art in social network data analytics. The book provides good coverage of the subject area by focusing on the most popular research topics, and offers numerous bibliographic references that will guide readers who are interested in particular topics. I highly recommend this book." (Aris Gkoulalas-Divanis, ACM Computing Reviews, August, 2011)