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.

Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.