Friday, July 31, 2015

Text Mining: #ksleg Followup

Last week's tweeting and blogging about mining the #ksleg (Kansas government related tweets) hashtag was a hit, so I decided to do it again.  First a wordcloud (because I know that's what everyone cares about)   It looks like Brownback, budget, audit, cut, and ksed (education) are hot topics.

And I used correlated topic modeling to model this weeks tweets as well.  What did I find?

This week, the algorithm only found three general topics in the data, and if you follow Kansas politics, these all make great sense:

  1. Covers the Kansas Legislative Post Audit committee's meeting, important news regarding a foster care audit.
  2. Covers issues with the Kansas education system, specifically regarding funding and teacher pay. 
  3. Covers a Thursday press conference, where the governor made additional budget cuts. 

And (this is psuedo-ironic-satire), the #ksleg hashtag tweeting leader-board for the week.  A tie for first place,  but BryanLowry3 wins in the "retweeted" tie breaker*

And, some example top tweets by topic above:

Topic 1: 

Topic 2:

Topic 3:

*Quick note for the data scientists, this bit of satire is easy to replicate for any twitter search term.  Essentially you use the twitteR library to download all the tweets, convert into a data frame, and then summarize the data. 

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