Social Network Data Analytics

Social network analysis applications have experience 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 (see list of contributors under Toc) presents a wide swath 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. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. Case studies will be provided as well.
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.