Advances in Network Clustering and Blockmodeling

1Introduction

Patrick Doreian^3,4, Vladimir Batagelj^1,2,5 and Anuška Ferligoj^3,5

¹IMFM Ljubljana

²IAM, University of Primorska, Koper

³FDV, University of Ljubljana

⁴University of Pittsburgh

⁵NRU HSE Moscow

This book focuses on network clustering regardless of the disciplines within which a network was 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. 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 network clustering. 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 reflect further on this in the concluding chapter. Here, we describe briefly the contents of the following chapters merely as an introduction to them. In our view, each chapter merits close attention.

1.1 On the Chapters

As the book is concerned with network clustering, ...