- 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 (View shipping rates and policies)
- Average Customer Review: 30 customer reviews
- Amazon Best Sellers Rank: #1,069,446 in Books (See Top 100 in Books)
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Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites 1st Edition
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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.
Top customer reviews
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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.
When originally attempting to enter this field, I found that I was overwhelmed with so many options in language, algorithm, business model, and catch phrase that I simply could not make progress. The beauty of this book is in its clear, concise progression from concept to concept that leaves the reader with a cohesive set of skills that are wildly marketable upon its completion.
The first friend I recommended this book to had almost no programming experience. 9 months later he landed a major deal mining social data for a major record label in Nashville.
If you've never programmed at all, this book can be a bit intimidating. I suggest reading it through first just to understand what can be done, and then to dive back in selectively to play with some code and tools he introduces you to when you know what most interests you. Given the arcania of the academic discourse about Big Data, graph databases, etc., the author has done a very good job of de-mystifying as well as de-jargoning. As a result, this book is widely accessible for a broad audience.
If you're interested in this topic, there is no better book to start with.
The book provides enough material to base further forays on. Not 5 stars because each analysis thread is left hanging a little bit. The book is methodology and process heavy and too lightweight in outcomes.
Most recent customer reviews
I was excited to read and try all the examples but I faced code problems related to the...Read more