Round Table

This book is focused on the network clustering regardless of the disciplines within which these networks were established. In the initial conception for the book, our attention was driven primarily by concerns regarding blockmodeling and community detection as they applied to social networks. But as we looked further into this general topic to invite potential contributors, we realized that the domain was much broader, both technically and substantively. The wide variety of approaches contained in this volume exemplifies this diversity. For us, as we assembled this volume, this was an exciting learning experience, one we hope will be experienced by readers of this book. There is no single best approach to clustering networks. Put differently, there is no cookie-cutter approach fitting all such data sets. Yes, there are adherents of one (their) approach who think this is the case. As shown in the chapters that follow, none of the authors of the contributed chapters share this very narrow view. This is a wide-open realm with multiple exciting approaches. We have much to learn from each other when freed from the restrictions imposed by academic departments, fields, sub-fields, and different specific approaches.

Here, is the content of the book:

• Introduction to the book Patrick Doreian, Vladimir Batagelj, and Anuška Ferligoj
• Bibliometric analyses of the network clustering literature Vladimir Batagelj, Anuška Ferligoj, and Patrick Doreian
• Clustering approaches to networks Vladimir Batagelj
• Different approaches to community detection Martin Rosvall, Jean-Charles Delvenne, Michael T. Schaub, and Renaud Lambiotte
• Label Propagation for Clustering Lovro Šubelj
• Partitioning valued network data Aleš Žiberna, and Carl Nordlund
• Treating missing network data before partitioning Anja Žnidaršič, Patrick Doreian, and Anuška Ferligoj
• Partitioning signed networks Vincent Traag, Patrick Doreian, and Andrej Mrvar
• Partitioning Multimode Networks Martin G Everett, and Stephen P Borgatti
• Blockmodeling Linked Networks Aleš Žiberna
• Bayesian stochastic blockmodeling Tiago P. Peixoto
• Structured networks and coarsegrained descriptions: a dynamical perspective Michael T. Schaub, Jean-Charles Delvenne, Renaud Lambiotte, and Mauricio Barahona
• Scientific coauthorship networks Marjan Cugmas, Anuška Ferligoj, and Luka Kronegger
• Conclusions and directions for future work Patrick Doreian, Anuška Ferligoj, and Vladimir Batagelj