I am placing this page here for my own future record and use… The original is available here.

Mining the Social Web, 2nd Edition – All Numbered Examples

This page provides a convenient catalog of all numbered examples that are included in the IPython Notebooks as part of this GitHub repository. Be sure to visit http://MiningTheSocialWeb.com for more updates, example code, and long-form content that didn’t make it into the book…

Chapter 1 – Mining Twitter

• Example 1. Authorizing an application to access Twitter account data
• Example 2. Retrieving trends
• Example 3. Displaying API responses as pretty-printed JSON
• Example 4. Computing the intersection of two sets of trends
• Example 5. Collecting search results
• Example 6. Extracting text, screen names, and hashtags from tweets
• Example 7. Creating a basic frequency distribution from the words in tweets
• Example 8. Using prettytable to display tuples in a nice tabular format
• Example 9. Calculating lexical diversity for tweets
• Example 10. Finding the most popular retweets
• Example 11. Looking up users who have retweeted a status
• Example 12. Plotting frequencies of words
• Example 13. Generating histograms of words, screen names, and hashtags
• Example 14. Generating a histogram of retweet counts
  

  Chapter 2 – Mining Facebook

• Example 1. Making Graph API requests over HTTP
• Example 2. Querying the Graph API with Python
• Example 3. Results for a Graph API query for Mining the Social Web
• Example 4. Querying the Graph API for Open Graph objects by their URLs
• Example 5. Comparing likes between Coke and Pepsi fan pages
• Example 6. Querying a page for its “feed” and “links” connections
• Example 7. Querying for all of your friends’ likes
• Example 8. Calculating the most popular likes among your friends
• Example 9. Calculating the most popular categories for likes among your friends
• Example 10. Calculating the number of likes for each friend and sorting by frequency
• Example 11. Finding common likes between an ego and its friendships in a social network
• Example 12. Calculating the friends most similar to an ego in a social network
• Example 13. Constructing a graph of mutual friendships
• Example 14. Finding and analyzing cliques in a graph of mutual friendships
• Example 15. Serializing a NetworkX graph to a file for consumption by D3
• Example 16. Visualizing a mutual friendship graph with D3
  

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