Update: An expanded version of this tutorial will appear in the new Elsevier book Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications by Gary Miner et. al which is now available for pre-order from Amazon.
In conjunction with the book, I have cleaned up the tutorial code and published it on github.
Last month I presented this introduction to R at the Boston Predictive Analytics MeetUp on Twitter Sentiment.
The goal of the presentation was to expose a first-time (but technically savvy) audience to working in R. The scenario we work through is to estimate the sentiment expressed in tweets about major U.S. airlines. Even with a tiny sample and a very crude algorithm (simply counting the number of positive vs. negative words), we find a believable result. We conclude by comparing our result with scores we scrape from the American Consumer Satisfaction Index web site
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