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Twitter Data Mining Round Up
Posted on February 10, 2014 Leave a Comment

Since the release of Mining the Social Web, 2E in late October of last year, I have mostly focused on creating supplemental content that focused on Twitter data. This seemed like a natural starting point given that the first chapter of the book is a gentle introduction to data mining with Twitter’s API coupled with […]
Mining Social Web APIs with IPython Notebook [Data Day Texas Workshop Slides]
Posted on January 12, 2014 Leave a Comment

Thanks to everyone who attended the Mining Social Web APIs with IPython Notebook workshop at Data Day Texas. I’m really glad that I made the trip down to Austin and could share some of my work with you. The data truly is bigger in Texas, Austin was a fantastic city to visit, and everyone I had […]
Understanding the Reaction to Amazon Prime Air (Or: Tapping Twitter’s Firehose for Fun and Profit with pandas)
Posted on December 19, 2013 2 Comments

On Cyber Monday eve, Jeff Bezos appeared in a 60 Minutes segment and revealed to the world that he’s been working on an experimental effort called Amazon Prime Air. The general idea behind Amazon Prime Air is that Amazon may one day deliver relatively lightweight items directly to your doorstep in less than 30 minutes […]
What Do Tim O’Reilly, Lady Gaga, and Marissa Mayer All Have In Common?
Posted on November 22, 2013 4 Comments

This post examines the followers of some popular Twitter users as the final installment of a multi-part series about exploring Twitter influence by asking the (Freakonomics-inspired) question, What do Tim O’Reilly, Lady Gaga, and Marissa Mayer all have in common? Although it may initially seem like an obnoxious question to ask, some of the answers may intrigue you […]
Super Simple Storage for Social Web Data with MongoDB (Computing Twitter Influence, Part 4)
Posted on November 20, 2013 3 Comments

In the last few posts for this series on computing twitter influence, we’ve reviewed some of the considerations in calculating a base metric for influence and how to acquire the necessary data to begin analysis. This post finishes up all of the prerequisite machinery before the real data science fun begins by introducing MongoDB as a […]
Getting Started with Twitter’s API: From Zero to Firehose in ~2.5 Minutes
Posted on November 12, 2013 4 Comments

Mining the Social Web‘s goal is to teach you how to transform curiosity into insight, and its virtual machine features two IPython Notebooks that are designed to get you up and running with Twitter’s API as quickly as possible. The following ~2.5 minute screencast shows how to generate OAuth credentials, establish a Twitter API connection, and make API […]
Twitter Could Be So Much Better Than An Advertising Company
Posted on November 11, 2013 2 Comments

If you’re a business with enough users, you can probably make some money by placing advertisements. Advertising drives commerce, and commerce is fundamental to a healthy economy. It’s a great and wonderful thing that profits are earned, jobs are created, taxes are paid, and a virtuous cycle develops around the commerce that results from advertising. […]
Mining Social Web APIs with IPython Notebook [Slides]
Posted on October 30, 2013 1 Comment

Thanks so much to everyone who attended the Mining Social Web APIs with IPython Notebook workshop. It was really inspiring to see so many of you get your hands dirty hacking on data (as opposed to just talking or thinking about it.) It’s a lot of work to design a 3 hour workshop for such […]
How To Harvest Millions of Twitter Profiles Without Violating the ToS (Computing Twitter Influence, Part 3)
Posted on October 22, 2013 1 Comment

In the last post in this continuing series on computing Twitter influence, we developed a wrapper function called make_twitter_request that handles the various sorts of HTTP error codes and network failures that you are likely to experience as you aspire to acquire non-trivial amounts of data from Twitter’s API. Although you are somewhat unlikely to […]
Why Is Twitter All the Rage?
Posted on October 9, 2013 4 Comments

Next week, I’ll be presenting a short webcast entitled Why Twitter Is All the Rage: A Data Miner’s Perspective that is loosely adapted from material that appears early in Mining the Social Web (2nd Ed). Given that the webcast is now less than a week away, I wanted to share out the content that inspired the topic. This […]