Mining the Social Web

    Mining the Social Web  (English, Paperback, Matthew A. Russell)

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    • Language: English
    • Binding: Paperback
    • Publisher: O'Reilly
    • ISBN: 9789350232941, 9350232941
    • Edition: 2011
    • Pages: 378
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    Mining The Social Web by Matthew A. Russell, is an invaluable guide which provides readers with an introduction to data mining and how to analyze the information from it.

    Summary Of The Book

    Mining The Social Web is a practical text which teaches users how to apply data mining techniques to the data collected from social networking sites such as LinkedIn, Facebook, and Twitter.

    The text will instruct readers how to put together data collected from various social networking sites, how to analyze this data, and other useful tidbits of information. The data mining techniques that are outlined in this text will help readers answer questions such as who is trying to connect via social media, what is being talked about, and where is the user’s location.

    Readers are required to have a basic knowledge in programming in order to grasp the techniques outlined in the book. Each chapter will show readers how to apply data mining techniques to different locations on the social web such as blogs, social rooms, and emails.

    The text has several salient features: it provides a summary about the social web arena, it teaches users how to apply scripts such as GitHub in order to harvest data from various social networks, and it shows users how to apply Python to the data that is collected. Readers will also learn how to explore the social web in microformats, apply data mining techniques such as cosine similarity, document summarization, clique detection, and TF-IDF. Using tool kits such as HTML5 and JavaScript, readers will be able to build interactive visualizations using web technologies.

    The text is divided into 10 chapters. Some of these chapter titles are Introduction To Hacking Data on Twitter, Microformats, Mailboxes, Twitter, LinkedIn: Clustering Your Professional Network for Fun, Google Buzz, Blogs, Facebook, and Semantic Web: A Cocktail Discussion. The topics covered in these chapters are Social Connections, Installing Python, Analyzing Mail Data, Analyzing Tweets, Visualizing Facebook Data, Buzzing on Bigrams, Clustering Networks, Sentence Detection, Entity-Centric Analysis, Data from Social Networks, and the NLP Pipeline.

    Mining The Social Web was published in 2011 by O’Reilly.

    About Matthew A. Russell

    Matthew A. Russell is an author, data miner, and computer scientist, who hails from Franklin, Tennessee.

    Some of these titles are Dojo Fundamentals: Creating Object-Oriented Widgets, 21 Recipes For Mining Twitter, Paypal APIs: Up and Running, Unleashing Twitter Data for Fun and Insight, and Dojo: The Definitive Guide.

    Matthew has extensive experience working for both the government and private sectors and has provided complex software at a budget. He is currently the Chief Technology Officer with Digital Reasoning Systems and also Zaffra’s Principal. Some of his areas of expertise are computer science, open source, developing web applications, and programming.

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    Book Details
    • Publication Year
      • 2011
    • Author
      • Matthew A. Russell
    3 Reviews
    • 5
    • 4
    • 3
    • 2
    • 1
    Most Helpful 
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    By Certified Buyers 

    good one

    Nice book with lot of worked examples in Python. Well written book - recommend this one but if you are buying your first social related book, recommend you buy "Programming Collective Intelligence" by Toby Segaran.That is better


    Certified Buyer

    20 Apr, 2015

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    Good book but context-less.

    Very abrupt discussions. Definitely not for beginners. Overall good. I wanted to buy something which is more seamless and had story. Now I hardly refer this.

    Saurabh Pandey

    Certified Buyer

    22 Dec, 2013

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    Good and hands on API and visualizing data. lot of fun in reading it.

    I found this book lot of fun and playing with published api of social networking sites. It also fun to visualize the data. I found the examples and code found in this book are different (some little code) from safari online version. example: searching for twitter trends through api is not exist now with latest api, safari version got updated version, but book has still old thing.

    Sandeep Nimmakuri

    Certified Buyer

    20 Aug, 2012

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