Experts in the field of social networks aim to help readers grasp the state of the art in the topic of network-based representation and analysis in this collection of papers. However, it is not a survey of this enormous area. Instead, the editors give readers a snapshot of recent work by presenting in each chapter a self-contained paper from different experts in the field.

The book consists of ten chapters and is part of the “Lecture Notes in Social Networks” (LNSN) series by Springer. In the first chapter, the editors introduce the topic of social networks, its nomenclature, its main analysis tools, and subtopics covered by the other chapters in the book. They classify the chapters that follow into six topics: “Node Analysis” (chapters 2 and 3), “Edge Analysis” (chapters 4 and 5), “Community Detection and Classification” (chapters 6 and 7), “Graph Crawling” (chapter 8), “Privacy and Social Networking Ethics” (chapter 9), and “Cloud Computing with Social Media” (chapter 10).

The chapters are of a very heterogeneous nature. Following the suggestion of the title of the book, they can be divided into two main classes: analysis and case studies. Some of the analysis chapters provide a good survey of a given topic. This is the case of chapter 6, where existing approaches for the detection of overlapping communities are reviewed. Other chapters in this category are very concise and leave the reader with the desire to know more about the subject, like the final chapter.

I found the case studies very interesting, especially the chapter “Social Networks and Group Effectiveness: The Role of External Network Ties.” This chapter discusses an ethnographic observation of three work groups in order to explore the relationship between group effectiveness and social networks. It is the only chapter in the book where social networks are taken in the traditional sense, which encompasses face-to-face interactions, and predates computer social networks.

I would recommend the book to anyone that wants to quickly get a grasp on the heterogeneity of subtopics that are studied in the social networks domain. However, it is not a survey of this domain, and it is not intended to cover all topics studied in the field. Most chapters have the format of conference papers, while some could be in a journal of social network surveys.