Statistical Analysis of Network Data with R (Use R!)

This is a great introduction to the 'igraph' package for R. Someone who is just a beginner in using R can probably use this book, but it's probably best to have already been using it for some time. The 'igraph' package is pretty extensive, but this book will give you enough tools to explore what else the package can do.It also covers the basics of doing network analyses. It doesn't go very deeply into any topics, really (nor does it have proofs or much theory), so it is best used in conjunction with (or perhaps after reading) Kolaczyk's other text  Statistical Analysis of Network Data . I used this after having used the other text.

Easy to understand and very comprehensive!

Easy to comprehend, concise code, and beautiful printing.

Great book for network analysis (although you need to know a little bit of R before you can use it).

Very good and concise introduction to the main statistical concepts you'll need to analyze networks and examples well integrated throughout.

I have 40 pages left to finish reading the book. So far, it seems to be like a very good book to get you inside the world of Social Network Analysis. The math in the book is easily "digestible" and the R code usually following the mathematical expressions substantially helps to understand the examples in the book. Overall, with 40 pages left, I quite like it.

as expected

Very useful book

This book is aimed at people with some knowledge of R and Social Network Analysis(SNA) and who want to use R for SNA in greater depth. It covers an impressive array of subjects and could be an indispensable text on the subject. For many like myself it is an attractive alternative to searching R's help pages for clues.Although, in the introduction, the authors claim that a modest knowledge of R is the only requirement it fails to explain many important steps along the way. It ends being an SNA primer (which for me was unnecessary and could not replace Wasserman and Faust 1994) punctuated by unexplained R code. You can figure out where the authors are going with the code if you then use the help function on R to get a full explanation but its not very user friendly. The 'sand' package which goes with the book is a nice idea although this really just saves you typing out the code yourself. Again if your aim is to understand the code this hardly helps. Perhaps the most annoying factor is that there is no instruction to load your own adjacency matrices. The explanations are based on toy graphs entered manually in R. As the author themselves admit this is not a likely method for using R to analyse your SNA data. Much more likely you will wish to load a spreadsheet (or CSV) file. Doing this is not simple as you then need R to coerce your data into a matrix/edgelist or whatever and make it into a graph object. This book does not tell you how to do this. This is a failure for an R SNA manual in my opinion. The O'Reilly R Cookbooks are much better in this sense but unfortunately there is not one for SNA.That said, its a quite useful manual for most SNA functions, once you can load your data!

The article arrived 2 days before designated date, in excellent condition.This book is one of the best A to Z guide to Network Analysis with comprehensive explanations of the codes and results.Regardless of the small volume, it provides exhaustive information on necessary steps of network investigation.