To some of its readers, this book is an introduction to social network analysis; to other readers, it is a manual to Pajek software (http://pajek.imfm.si/doku.php). To us, it is both. As Patrick Doreian argued in his review of our book [In: Social Networks 28 (2006) 269–274], an understanding of social network analysis is required for proper use of Pajek, and, vice versa, understanding the concepts and logic of Pajek fosters comprehension of network concepts. In this second edition, we have aimed to strengthen both aspects, updating the discussion of the Pajek interface and commands to include several capabilities that have been implemented since we submitted the text of the first edition, such as multiplex networks (Section 1.3.1), eigenvector centrality (Section 6.5), matrix multiplication (Section 11.3), and using Pajek output in R (Chapters 5 and 13). The new capabilities cover some important advances in social network analysis, including random graph models to which we have dedicated a new chapter.