This is the first textbook on social network analysis integrating theory, applications, and professional software for performing network analysis (Pajek). Pajek software and datasets for all examples are freely available, so the reader can learn network analysis by doing it. In addition, each chapter offers case studies for practicing network analysis. The book will enable the reader to gain the knowledge, skills, and tools to apply social network analysis in all social sciences, ranging from anthropology and sociology to business administration and history.
Pajek becomes a necessary tool when using large samples in social network analysis. Unfortunately, finding basic, comprehensive tutorials and user guides either within the software itself (UCINET is extremely commendable by comparison for this reason alone) or elsewhere is nearly impossible. Ironically, while the software is free, the guide is not. And, should you find yourself having to use Pajek, this book is a very useful, basic guide to the program. Chapters break down various components of larger analytical procedures (such as calculating centrality or identifying cliques), and provide simple examples as well as the order of commands needed to perform the function in the software itself. Each chapter concludes with a set of practice questions and explanations. The book also includes chapters on software and file management such as saving program files and printing visualizations.
I do have two complaints about this text, however. The first is that, some of the network examples and practice questions correspond to pre-fabricated data files that are not included with the book say, for example, as a CD-Rom where you could load files onto your desktop. Moreover, despite Pajek being a valuable tool for dealing with large networks, the text largely deals with analysis of very small samples. Granted, there is a feasibility not only in examining, but illustrating such small networks, but very few tutorials will provide guidelines and outline the caveats of dealing with larger networks.
Despite this, for those who are new to social networking analysis and particularly the software side and using Pajek, this is a good starting point that is easy to understand.
This is a valuable resource for those interested in social networks analysis. The book not only contains the better guide available to use PAJEK (one of the most popular softwares to hanle social network data) but a excellent presentations of the key concepts and types of analysis in the field. Last but not least, the price is very affordable.
This is both an introduction to social networks theory and a friendly Pajek manual written by Pajek's own creator (and others).Well written and illustrated, the book covers the central concepts in the field and guides the reader through a powerful and elegant program which is also freely available on the internet. After reading only three chapters (1,2 and 11) I am applying it to my own ethnographic data with interesting results. A good book!
It is a very helpful book with many examples and online metarials for Pajek learners.
Pajek means spider in Slovenian. Pajek is also a software program for the analysis and visualisation of very large networks; networks with thousands if not millions of vertices. It is a program I use occasionally, however I prefer UCINET and NetMiner 3 , because I find these programs to be easier to use. It is precisely for this reason I bought and read "Exploratory Social Network Analysis with Pajek" by Wouter de Nooy, Andrej Mrvar, and Vladimir Batagelj.
The book is an easy read and nicely complements the manual - in fact I think it could easily replace the manual.
I learnt that Pajek is actually quite a bite easier to use than I first thought. Having played around with Pajek after reading the book I found I could manipulate my datasets in new ways. That said I am not a convert to Pajek.
I did like the examples and the explanations that went with them. Even if I never use Pajek again the book is useful simply because the examples explain rather than describe many of the complexities and pitfalls of network analysis. Read in conjunction with other publications like Wassermann and Faust's "Social Network Analysis. Methods and Applications" the student of network analysis should gain a solid theoretical understanding of network analysis and be able to read network studies more critically. I also found the many exercises in the book most useful. They progressively built and reinforced understanding and competence in Pajek, as well as understanding of network ideas.
So all in all I would give the book a five-star rating - five stars for readability and five stars for the learning by doing approach. It has a place on the bookshelf of even serious student of network analysis.
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