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Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites Paperback – February 11, 2011

ISBN-13: 978-1449388348 ISBN-10: 1449388345 Edition: 1st

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Product Details

  • Paperback: 356 pages
  • Publisher: O'Reilly Media; 1 edition (February 11, 2011)
  • Language: English
  • ISBN-10: 1449388345
  • ISBN-13: 978-1449388348
  • Product Dimensions: 7 x 0.9 x 9.2 inches
  • Shipping Weight: 1.3 pounds
  • Average Customer Review: 4.1 out of 5 stars  See all reviews (27 customer reviews)
  • Amazon Best Sellers Rank: #681,175 in Books (See Top 100 in Books)

Editorial Reviews

Book Description

Finding Needles in the Social Haystack

About the Author

Matthew Russell, Chief Technology Officer at Digital Reasoning, Principal at Zaffra, and author of several books on technology including Mining the Social Web (O'Reilly, 2013), now in its second edition. He is passionate about open source software development, data mining, and creating technology to amplify human intelligence. Matthew studied computer science and jumped out of airplanes at the United States Air Force Academy. When not solving hard problems, he enjoys practicing Bikram Hot Yoga, CrossFitting and participating in triathlons.


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Customer Reviews

The book is well written and manages to keep me interested and motivated, which is great.
rickm
Mining the Social Web by Matthew Russell is a delightful reading which covers a wide array of very pertinent social media technologies.
Adnan Masood
Some basic programming ability is a must for this book, as the first page starts with installing the Python development tools.
Wiebe de Jong

Most Helpful Customer Reviews

26 of 27 people found the following review helpful By H. Smith on March 3, 2011
Format: Paperback Verified Purchase
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. It offers a nice compliment to Segaran's Programming Collective Intelligence: Building Smart Web 2.0 Applications. The two books overlap but where they do offer different perspectives and explanations of common techniques (e.g., TF-IDF, cosine similarity, Jaccard index). If you are well-versed in data mining the web you may find much of the discussion familiar. If you have only been casually engaged to date, your toolbox will fill quickly.

In order to work with the book's examples related to LinkedIn and Facebook you really need to have a robust collection of connections. In terms of the source code itself, most of it worked as is. I wasn't able to install the Buzz library which limited my interaction with material in chapter 7 and opted to not get involved with the LinkedIn or Facebook but found the discussions around them easy to follow. By far my favorite chapter in the book was chapter 8, "Blogs et al.: Natural Language Processing (and Beyond)..." It was quite fascinating and caused my reading list to grow considerably.
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17 of 18 people found the following review helpful By Ricardo Bánffy on February 7, 2011
Format: Paperback
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.
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10 of 10 people found the following review helpful By Wiebe de Jong on March 8, 2011
Format: Paperback
Some basic programming ability is a must for this book, as the first page starts with installing the Python development tools. If you don't 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.

Once you get comfortable with the basics, the author quickly moves from topic to topic, giving a good introduction into many aspects of how to mine data and generate useful conclusions. Some of the examples include

accessing your twitter feed with OAuth,
processing feeds to determine influence,
using set-wise opeations with redis to determine which of your friends are also followers,
storing data in CouchDB,
using map-reduce to determine the most popular mentions and topics,
natural language processing,
and seeing data with various visualization tools.

And that was just for Twitter.

The book continues on with examples of processing mailboxes, LinkedIn, Google Buzz, blogs, Facebook, and the Semantic Web. The examples show how easy it is to gather and analyze data from all these social web sites.

With a good breadth of coverage, I highly recommend this book for anyone wanting to learn to process and visualize large amounts of data, either from the social web or any other data source.
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7 of 8 people found the following review helpful By Eric B. Harding on February 8, 2011
Format: Kindle Edition
Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites.
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. To get the most out of this book you will need to install and run Python on your computer (be it a Mac, Window or Linux based machine). If you have not been scared off by that, then you are in for some fun manipulating (really just reporting on) Social Media site data.

The Author does a very good job of outlining the prerequisites for the book, going though the process of installing Python and even a little troubleshooting to get it working properly. The Author takes this same care throughout the book, making few assumptions about the skill level of the reader, but also keeping it interesting for the more advanced readers as well. One unexpected example was mining your own mailbox, the original Social Media. The Mailbox examples are pretty extensive, if you make it through those then you should have little trouble with the remaining examples, which attack Facebook, Twitter, LinkedIn and Google Buzz. The book's examples can induce a certain amount of narcissism, but thats the heart to social media and not intended as a criticism of the book. However there are enough outward looking examples to stop you from becoming to self absorbed. As well the graphing examples provide some eye candy for the reader.

In closing, the book gives the reader a good understanding of Social Media data and what can be done with it.
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