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.
Exploratory Social Network Analysis with Pajek
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"Exploratory Social Network Analysis with Pajek, is an introduction to both network analysis in general and to the Pajek package in particular. It is an excellent book for the beginner: clearly written, well presented, comprehensive and engaging." -Nick Crossley, Sociology
Book Description
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. In the end, the reader has the knowledge, skills, and tools to apply social network analysis in all social sciences, ranging from anthropology and sociology to business administration and history.
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Most Helpful Customer Reviews
10 of 10 people found the following review helpful:
5.0 out of 5 stars
Plain-English guidance for excellent software,
By
This review is from: Exploratory Social Network Analysis with Pajek (Structural Analysis in the Social Sciences) (Paperback)
This book comes so highly recommended because it lowers all the barriers for the student. The text is easily absorbed, the software is free, and the datasets are there. Many guides on Social Network Analysis (SNA) seem like they are written for someone who already knows how to do SNA. The original Pajek manual is one example (Pajek is pronounced pai-yak). This book is like the missing manual. It guides the novice carefully through the analysis process. The free software, Pajek, is one of the best Social Network programs currently. Although Pajek was initially just for visualizations of large networks, and it still only has a subset of the UCInet functions, the algorithms are fast and plentiful. The book and software should keep a student busy until they add more programmatic SNA tools to their toolkit (e.g. R-project sna).
7 of 7 people found the following review helpful:
5.0 out of 5 stars
Pajek - A Must Read for Network Analysts,
By G. A. Durant-law "Graham Durant-Law" (Canberra, Australia) - See all my reviews
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This review is from: Exploratory Social Network Analysis with Pajek (Structural Analysis in the Social Sciences) (Paperback)
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. Regards, Graham
11 of 13 people found the following review helpful:
5.0 out of 5 stars
A really exellent textbook and manual,
By
This review is from: Exploratory Social Network Analysis with Pajek (Structural Analysis in the Social Sciences) (Paperback)
I am dipping my toe into the world of networks analysis and this was the perfect way to learn about them and to learn how to use an excellent software package (which is free!) The book is well written and structured with examples to play with and excellent data sets to download from the web.
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Inside This Book
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First Sentence:
Social network analysis focuses on ties among, for example, people, groups of people, organizations, and countries. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
structural prestige, traversal weights, proximity prestige, exploratory social network analysis, dyadic constraint, strong semiperiphery, hierarchical clusters model, visiting ties, ranked clusters model, shrunk network, simple directed network, complete subnetworks, bidirected arcs, closeness centrality scores, induced subnetwork, closeness centralization, null dyads, energized drawing, maximal subnetwork, new empty partition, vertices that belong, betweenness centralization, math network, nobility genealogy, cohesive subgroups Key Phrases - Capitalized Phrases (CAPs): (learn more)
Petrus Gondola, John Bosco, San Juan Sur, Extract Second, South American, Answers Answers, New York, Fruchterman Reingold, Application Net, Cambridge University Press, Editing Network, Hierarchy Edit, Random Start, The Free Press, Loyal Opposition, Make Partition, Partition Colors, French Guiana, Make Vector, North American, Shrink Network, Export Matrix, Extract Subvector, John Scott, Mark Vertices Using New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Social network analysis focuses on ties among, for example, people, groups of people, organizations, and countries. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
structural prestige, traversal weights, proximity prestige, exploratory social network analysis, dyadic constraint, strong semiperiphery, hierarchical clusters model, visiting ties, ranked clusters model, shrunk network, simple directed network, complete subnetworks, bidirected arcs, closeness centrality scores, induced subnetwork, closeness centralization, null dyads, energized drawing, maximal subnetwork, new empty partition, vertices that belong, betweenness centralization, math network, nobility genealogy, cohesive subgroups Key Phrases - Capitalized Phrases (CAPs): (learn more)
Petrus Gondola, John Bosco, San Juan Sur, Extract Second, South American, Answers Answers, New York, Fruchterman Reingold, Application Net, Cambridge University Press, Editing Network, Hierarchy Edit, Random Start, The Free Press, Loyal Opposition, Make Partition, Partition Colors, French Guiana, Make Vector, North American, Shrink Network, Export Matrix, Extract Subvector, John Scott, Mark Vertices Using New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 38
books:
See all 38 books this book cites
4
books
cite this book:
- Social Network Analysis: Methods and Applications (Structural Analysis in the Social Sciences) by Stanley Wasserman on 9 pages
- Social Network Analysis: A Handbook by John P Scott on 5 pages
- Network Analysis (Quantitative Applications in the Social Sciences) by David Knoke in Front Matter, page 181, and page 201
- Introducing Social Networks (Introducing Statistical Methods series) by Alain Degenne on page 135, page 157, and page 288
- Applied Network Analysis: A Methodological Introduction by Ronald S. Burt on page 181, and page 201
See all 38 books this book cites
- Models and Methods in Social Network Analysis (Structural Analysis in the Social Sciences) by Peter J. Carrington on page 97, and page 314
- Graph Drawing Software (Mathematics and Visualization) by Michael Jünger on page 79, and page 102
- Generalized Blockmodeling (Structural Analysis in the Social Sciences) by Patrick Doreian in Back Matter
- Graph Drawing: 9th International Symposium, GD 2001 Vienna, Austria, September 23-26, 2001, Revised Papers (Lecture Notes in Computer Science) by Petra Mutzel on page 478
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