This book redefines community discovery in the new world of Online Social Networks and Web 2.0 applications, through real-world problems and applications in the context of the Web, pointing out the current and future challenges of the field.

Particular emphasis is placed on the issues of community representation, efficiency and scalability, detection of communities in hypergraphs, such as multi-mode and multi-relational networks, characterization of social media communities and online privacy aspects of online communities.

User Community Discovery is for computer scientists, data scientists, social scientists and complex systems researchers, as well as students within these disciplines, while the connections to real-world problem settings and applications makes the book appealing for engineers and practitioners in the industry, in particular those interested in the highly attractive fields of data science and big data analytics.

Redefines community discovery in the new world of Online Social Networks and Web 2.0 applications Provides methods to handle the complexity of multi-relational and multi-mode graphs, such as the social networks Presents the use of state-of-the-art methods for community discovery in the Social Web, e.g. matrix factorization, hypergraph analysis, and consensus clustering. Includes supplementary material: sn.pub/extras

Inhalt

Preface.- List of Reviewers.- List of Contributors.- Discovery of Complex User Communities.- Community Discovery: Simple and Scalable Approaches.- Community Discovery in Multi-Mode Networks.- Discovering Communities in Multi-relational Networks.- Group Types in Social Media.- Privacy Issues in Discovering Communities in Social Networks.