21 Recipes for Mining Twitter: Distilling Rich Information from Messy Data 1st Edition

by Matthew A. Russell (Author)

8 customer reviews

ISBN-13: 978-1449303167

ISBN-10: 9781449303167

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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.

Editorial Reviews

About the Author

Matthew Russell, Vice President of Engineering at Digital Reasoning Systems (http://www.digitalreasoning.com/) and Principal at Zaffra (http://zaffra.com), is a computer scientist who is passionate about data mining, open source, and web application technologies. He’s also the author of Dojo: The Definitive Guide (O’Reilly).

Paperback: 76 pages
Publisher: O'Reilly Media; 1 edition (March 10, 2011)
Language: English
ISBN-10: 9781449303167
ISBN-13: 978-1449303167
ASIN: 1449303161
Product Dimensions: 7 x 0.2 x 9.2 inches
Shipping Weight: 4.8 ounces (View shipping rates and policies)
Average Customer Review: 8 customer reviews
Amazon Best Sellers Rank: #1,792,201 in Books (See Top 100 in Books)
- #366 in Books > Computers & Technology > Computer Science > Computer Simulation
- #405 in Books > Computers & Technology > Computer Science > Information Theory
- #916 in Books > Computers & Technology > Databases & Big Data > Data Modeling & Design

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bamazon

Very Practical

June 14, 2011

Format: PaperbackVerified Purchase

There is not much fluff in this book. It has very practical examples that work right out of the box.

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Amazon Customer

Five Stars

February 20, 2016

Format: PaperbackVerified Purchase

Great book

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Polyglot

Pretty good as long as you don't mind ignoring all of the code samples in the book

February 11, 2012

Format: PaperbackVerified Purchase

The Python twitter API had a major change a few months ago that totally invalidated the code samples in this book. Fortunately, there are direct links in the book to freely available updated versions of the code on github.com.

Oh well.

4 people found this helpful

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Harvey Sugar

60 Pages of Content

April 4, 2011

Format: PaperbackVerified Purchase

It's my own fault. I should have read the description closely. The book is only 72 pages long including all the front matter and O'Reilly's advertising in the back. So it's just 60 pages of actual content for over $29.

O'Reilly should be ashamed pricing this book at $29.

9 people found this helpful

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Ricardo Bánffy

Matthew Russell's 21 Recipes for Mining Twitter

April 25, 2011

Format: Paperback

This is a very short, very practical way to get you started exploring the Twitter APIs on your own. It offers a decent amount of code no experienced developer should have much trouble understanding and applying to his or her own needs. The cost per page is not exactly attractive and some readers may want a more in-depth less cookbook-like experience. If you are in a hurry to extract data from Twitter, this book may be for you - for less than $20 for the electronic edition, it will spare you more than that in time spent figuring out libraries and APIs. Plus, it offers some intro on many other interesting libraries that can be applied to a lot of problems besides Twitter mining.

3 people found this helpful

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Chris Miller (@IdoNotes)

Free code, to the point, just what you want to get started

March 22, 2011

Format: Paperback

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.

One person found this helpful

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Bill Day

21 Recipes for Mining Twitter by Matthew Russell

March 14, 2011

Format: Paperback

"21 Recipes for Mining Twitter" by Matthew Russell provides readers with a problem-oriented crash course in using Python and freely available third party Python packages to mine social data from Twitter. It assumes familiarity with Python and makes quick progress through extracting and using different types of user and streaming data available from the Twitter API via the twitter package in particular.

I like the general approach of calling out problems to be solved, then addressing them one by one with a "recipe" for each. Some might complain that this approach results in disjointedness from one recipe to the next, but in fact that's a feature, not a bug. "21 Recipes for Mining Twitter" is actually a spin-off of Russell's more in depth "Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites" (also an O'Reilly book). The latter shows many more examples, and not just for mining Twitter, but also for harvesting and analyzing social data from many other services and APIs as well. So if you need down-and-dirty recipes for Twitter alone, get this book, and if you need more blanks filled in for Twitter mining and/or information on accessing data from other social services, get the other book. Or heck, get them both!

This book is recommended for: Anyone already familiar with programming who is looking to solve specific problems using Twitter data. It's a slam dunk for Python programmers.

Recommended with reservations for: Non-programmers interested in social data analysis, with the caveat that they will probably need to spend some time working through the Python.org tutorial or getting up to speed with Python elsewhere before they can make great progress with this book.

Disclaimer: I know the author and have worked with him in various capacities on other projects, but not this book. Even if I didn't know him, however, I'd still love and make use of this book.

5 people found this helpful

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Wanzi

Decent

September 4, 2011

Format: PaperbackVerified Purchase

There is no problem with the book, just a little tough for those new to Python. I would recommend this for those who know Python, but encourage those who don't to be prepared for a couple hours.

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