Media praise for Mining the Social Web

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"Kudos to the organization of the book, with chapter 'encapsulation', allowing for each chapter to be read independently, for each social web network. The e-book is enjoyable because it has a lot of hyperlinks, which is quite convenient..."
-- Doron Katz,

"This fast-paced and rich handbook jumps right into the fray and provides an immediate and useful exercise in accessing the Twitter API using python and doing a very quick visualization of trending subjects. I was hooked and greedily and immediately consumed a few more of his lessons. "
-- Shawn Day, randomosity

"I got out of my comfort zone and learned several things from this book, so I recommend it to all readers who need to improve their understanding of data."
-- Jeremy Schultz, Designorati

"This book is unique in that it not only provides a classic tutorial on the concepts and algorithms for analyzing social relationships and the content created by people on the Web, but also offers readers the right tools for doing such an analysis."
-- Maria Bielikova, Computing Reviews, STU Bratislava, Slovakia

"Mining the Social Web is a good start for anyone is going to create scripts to analyze patterns in Social Networks. I've to say that this book consider that the reader already masters Python. I think that should be written directly on the title (ie: "Mining the Social Web with Python"Ě)." Full Review >
-- Fabio Alessandro Locati,

"'Mining the Social Web' by Matthew Russell provides an interesting introduction into the world of data analysis using Python. There are many examples for mining many of the most popular social networks and plenty of in-depth instructions to ensure that even those with a basic understanding of programming should be able to get up and running fairly quickly. The book begins with an explanation of how to best set up the Python development tools, and then launches into tactics for the harvesting and in-depth analysis of data, generated by using social web APIs, Python tools, GitHub, HTML5, and JavaScript." Full Review >
-- Jonathan Hume,

"This book contains how to retrieve userdata from Twitter, LinkedIn, Google Buzz via Web API using the corresponding public python library. Technologically, microformat, k-means clustering, Natural Language Processing, ranking algorithm, how to find similar documents are also explained by using practical SNS datas. The corresponding sections contain a summary of each algorithm. All implementation is based on python, so readers need to understand very well beforehand. Totally, though the explanation is summary level and doesn't dive into deeply, it is nice entry point to start to dive into text mining not only SNS but also unstructured documents." Full Review >
-- Hitoshi Uchida,

"Some basic programming ability is a must for this book, as the first page starts with installing the Python development tools. If you donít know Python, that is okay since all the code is easy to follow. Everything you need to develop and run the examples is described step by step with clear instructions at every point." Full Review >
-- Wiebe de Jong,

"Mining the Social Web is a guide to using Python and related tools to make sense out of data from Twitter, Facebook, and other Social Media and Web data. Redis, CouchDB and the Natural Language Tool Kit are covered, as well as the APIs of the various services." Full Review >
-- Norman DeValliere,

"Mining the Social Web by Matthew Russell, published by OíReilly, is an overview of data mining popular websites such as Twitter, Facebook, Linkedin and more. It even goes as far as touching on the semantic web and the not-so-popular Google Buzz." Full Review >
-- David Bowers,

"Mining the Social Web does a great job of introducing a wide variety of techniques and wealth of resources for exploring freely available social data and personal information. If you are willing to spend the time tinkering with the examples, the book is pure fun." Full Review >
-- Hal Smith,

"Mining the Social Web (by Matthew A. Russell) is very aptly named. The reader will get their hands dirty "mining" the Social Web. If you are not comfortable writing or reading Python script than this probably is not be the book for you. " Full Review >
-- Eric Harding,

"This book covers a lot of ground. It's, at times, a bit vertiginous in the amount of subjects and technologies it touches per chapter, and is not always easy to follow. It can also introduce so many interesting things that, by the time you finished becoming familiar with all of them, after wandering for hours on the web, jumping from interesting technology to interesting technology, you may have forgotten what took you to these places and wonder where you were in the book. Time spent reading it is, however, time very well spent. When you finish it, you will have at least a cursory familiarity with tools like OAuth, CouchDB, Redis, MapReduce, NumPy (and the Python programming language, albeit it will help you a lot if you know your way around Python before you start the book), Graphviz, SIMILE widgets, NLTK, various service APIs and data formats, and will be well equipped to explore those rich datasets on your own. The chapters are well compartmentalized and it's easy to pick chapters to read according to your needs. I know that, when I face the problems they tackle, I will do exactly that. If you do any kind of analysis and visualization of social-generated data that's on the web, this book is a good pick. Even if your datasets are not from the web, you may find the parts on analysis and visualization very interesting." Full Review >
-- Ricardo Banffy,

"This is a very comprehensive and thoughtful approach to the avalanche of explorable data available from our social existence and Russell provides an extremely approachable and superbly crafted volume. For anyone interested in stepping beyond simple participation and taking a thoughtful view of how social media is changing our lives, this is the book of reference." Full Review >
-- Shawn Day,

"Hot off the press this month, this book combines techniques and methods for aggregating and mining data from the most popular Social Networks, such as LinkedIn, Facebook and Twitter. Written as a cookbook, the author does not hide the fact that the reader will have to get 'knee-deep' in Python development, and to be a bit savvy in Javascript/HTML5 is also advisable. " Full Review >
-- Doron Katz,

"A good primer on capturing and visualizing social data, and tools to do more with what you find. Not for the faint of heart.The book's title may be deceptive outside the worlds of web design or data analysis. A prerequisite knowledge of getting around in Python is a must from..." Full Review >
-- Isaac Fischer,