Books & Videos

Table of Contents

  1. A Guided Tour of the Social Web

    1. Prelude

    2. Chapter 1 Mining Twitter: Exploring Trending Topics, Discovering What People Are Talking About, and More

      1. Overview
      2. Why Is Twitter All the Rage?
      3. Exploring Twitter's API
      4. Analyzing the 140 Characters
      5. Closing Remarks
      6. Recommended Exercises
      7. Online Resources
    3. Chapter 2 Mining Facebook: Analyzing Fan Pages, Examining Friendships, and More

      1. Overview
      2. Exploring Facebook's Social Graph API
      3. Analyzing Social Graph Connections
      4. Closing Remarks
      5. Recommended Exercises
      6. Online Resources
    4. Chapter 3 Mining LinkedIn: Faceting Job Titles, Clustering Colleagues, and More

      1. Overview
      2. Exploring the LinkedIn API
      3. Crash Course on Clustering Data
      4. Closing Remarks
      5. Recommended Exercises
      6. Online Resources
    5. Chapter 4 Mining Google+: Computing Document Similarity, Extracting Collocations, and More

      1. Overview
      2. Exploring the Google+ API
      3. A Whiz-Bang Introduction to TF-IDF
      4. Querying Human Language Data with TF-IDF
      5. Closing Remarks
      6. Recommended Exercises
      7. Online Resources
    6. Chapter 5 Mining Web Pages: Using Natural Language Processing to Understand Human Language, Summarize Blog Posts, and More

      1. Overview
      2. Scraping, Parsing, and Crawling the Web
      3. Discovering Semantics by Decoding Syntax
      4. Entity-Centric Analysis: A Paradigm Shift
      5. Quality of Analytics for Processing Human Language Data
      6. Closing Remarks
      7. Recommended Exercises
      8. Online Resources
    7. Chapter 6 Mining Mailboxes: Analyzing Who's Talking to Whom About What, How Often, and More

      1. Overview
      2. Obtaining and Processing a Mail Corpus
      3. Analyzing the Enron Corpus
      4. Discovering and Visualizing Time-Series Trends
      5. Analyzing Your Own Mail Data
      6. Closing Remarks
      7. Recommended Exercises
      8. Online Resources
    8. Chapter 7 Mining GitHub: Inspecting Software Collaboration Habits, Building Interest Graphs, and More

      1. Overview
      2. Exploring GitHub's API
      3. Modeling Data with Property Graphs
      4. Analyzing GitHub Interest Graphs
      5. Closing Remarks
      6. Recommended Exercises
      7. Online Resources
    9. Chapter 8 Mining the Semantically Marked-Up Web: Extracting Microformats, Inferencing over RDF, and More

      1. Overview
      2. Microformats: Easy-to-Implement Metadata
      3. From Semantic Markup to Semantic Web: A Brief Interlude
      4. The Semantic Web: An Evolutionary Revolution
      5. Closing Remarks
      6. Recommended Exercises
      7. Online Resources
  2. Twitter Cookbook

    1. Chapter 9 Twitter Cookbook

      1. Accessing Twitter's API for Development Purposes
      2. Doing the OAuth Dance to Access Twitter’s API for Production Purposes
      3. Discovering the Trending Topics
      4. Searching for Tweets
      5. Constructing Convenient Function Calls
      6. Saving and Restoring JSON Data with Text Files
      7. Saving and Accessing JSON Data with MongoDB
      8. Sampling the Twitter Firehose with the Streaming API
      9. Collecting Time-Series Data
      10. Extracting Tweet Entities
      11. Finding the Most Popular Tweets in a Collection of Tweets
      12. Finding the Most Popular Tweet Entities in a Collection of Tweets
      13. Tabulating Frequency Analysis
      14. Finding Users Who Have Retweeted a Status
      15. Extracting a Retweet’s Attribution
      16. Making Robust Twitter Requests
      17. Resolving User Profile Information
      18. Extracting Tweet Entities from Arbitrary Text
      19. Getting All Friends or Followers for a User
      20. Analyzing a User’s Friends and Followers
      21. Harvesting a User’s Tweets
      22. Crawling a Friendship Graph
      23. Analyzing Tweet Content
      24. Summarizing Link Targets
      25. Analyzing a User’s Favorite Tweets
      26. Closing Remarks
      27. Recommended Exercises
      28. Online Resources
  3. Appendixes

    1. Appendix Information About This Book's Virtual Machine Experience

    2. Appendix OAuth Primer

      1. Overview
    3. Appendix Python and IPython Notebook Tips & Tricks

  1. Colophon