21 Recipes for Mining Twitter
Distilling Rich Information from Messy Data
Publisher: O'Reilly Media
Final Release Date: January 2011
Pages: 76

Millions of public Twitter streams harbor a wealth of data, and once you mine them, you can gain some valuable insights. This short and concise book offers a collection of recipes to help you extract nuggets of Twitter information using easy-to-learn Python tools. Each recipe offers a discussion of how and why the solution works, so you can quickly adapt it to fit your particular needs. The recipes include techniques to:

  • Use OAuth to access Twitter data
  • Create and analyze graphs of retweet relationships
  • Use the streaming API to harvest tweets in realtime
  • Harvest and analyze friends and followers
  • Discover friendship cliques
  • Summarize webpages from short URLs

This book is a perfect companion to O’Reilly's Mining the Social Web.

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O'Reilly Media21 Recipes for Mining Twitter
 
3.0

(based on 3 reviews)

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1.0

CODE DEPRECATED: Do Not Buy!

By John

from Guildford, UK

About Me Data Scientist

Verified Reviewer

Pros

    Cons

    • Code Is Deprecated
    • Very Limited Usability

    Best Uses

    • Time Traveller

    Comments about O'Reilly Media 21 Recipes for Mining Twitter:

    Do not buy this title!

    Please note that code examples within this book were written for the now deprecated V1 Twitter API.

    The author himself notes at:

    https://github.com/ptwobrussell/Recipes-for-Mining-Twitter

    that the title is "now defunct", and recommends that you instead purchase his (also very good) "Mining the Social Web Ed.2", at:

    http://shop.oreilly.com/product/0636920030195.do?cmp=af-strata-books-video-product_cj_0636920030195_7133220

    I love many O'Reilly titles, including this one (back in 2011), but at this point O'Reilly should remove this title from sale.

    I hope that this review helps you spend more effectively.

    Warm Regards,
    John

     
    4.0

    No fluff with free code examples

    By IdoNotes

    from St Louis, MO

    About Me Reviewer, Sys Admin

    Verified Reviewer

    Pros

    • Concise
    • Helpful examples

    Cons

      Best Uses

      • Expert
      • Intermediate

      Comments about O'Reilly Media 21 Recipes for Mining Twitter:

      The book 21 Recipes for Mining Twitter is an add-on to another book I am reviewing by Matthew Russell, Mining the Social Web.

      This small, yet incredibly useful, book covers 21 tips and accompanying code for mining Twitter data. There is no fluff in this 60 page book with page 1 diving right into OAuth access.

      Each of the tips (recipes) start with the problem , a brief solution and then the lengthy solution and code samples to bring the two together. Everything in the book is written in Python with much of it being made accessible via easy_install.

      While the majority of this book is code, it is an incredible companion to get you moving in pulling data, trends or just about anything from Twitter. Creating and analyzing graphs becomes easier, discovering friendships and cliques, pulling geo-data and even finding a retweet's source.

      Much of the metadata we produce via Twitter gets lost instantly, since no one digs and mines the underlying data. This book can help you build some product or service you want around Twitter and hands you basic code to get you started. The book 21 Recipes for Mining Twitter is a great resource.

      (1 of 1 customers found this review helpful)

       
      4.0

      Full of tips to start mining twitter

      By jsanpedro

      from State College, PA

      About Me Researcher

      Verified Reviewer

      Pros

      • Concise
      • Helpful examples

      Cons

      • Assumes API knowledge

      Best Uses

      • Intermediate
      • Novice

      Comments about O'Reilly Media 21 Recipes for Mining Twitter:

      This book provides readers with a quite comprehensive introduction to extracting and analyzing information from Twitter. While it is expected that the reader is somewhat familiar with the different Twitter APIs, the author does a fantastic job at presenting strategies for crawling and mining data using python and some additional and freely available third party libraries.

      The main three aspects that I loved about this little gem were:

      - The author does a great job at highlighting the main Twitter's API limitations (e.g. maximum number of requests for each API call) and bugs (e.g. user ids being different in the '/search' API). Solutions, in the form of functional code, are given. This information can save literally hours debugging code or waiting for twitter to remove restrictions imposed after going beyond some of the limits imposed by the system.

      - All the code, available for free from the author's github.com account, is very well conceived, illustrative and most of the time can be used directly from the command line to perform simple tasks with Twitter's data.

      - Lots of 3rd party libraries and tools (e.g. CouchDB, Redis, Protovis, etc.) are introduced to the reader, and used in appropriate contexts. That is, when they actually make the code easier to read, or simply more flexible in terms of scalability. I've learned quite a few tricks that are changing the way I work with data (and not just twitter data).

      On the other hand, I really missed a short introduction to the main Twitter APIs. It's confusing to read about "statuses" or "timelines" without a prior formal definition. It took me quite some time to distill the appropriate information from the Twitter's developer documentation.

      A must read if you are planning to work with Twitter data.

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