Blog Archives

Minute by Minute Twitter Sentiment Timeline from the VP debate

October 12, 2012
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Minute by Minute Twitter Sentiment Timeline from the VP debate

Click on above graph to enlarge. Background The data for this graph was collected automatically every ~60 seconds of the VP debate on 10/11/2012, with an ending aggregate sample size of 363,163 tweets.  From this dataset duplicate tweets were removed (because of bots), which gave a final dataset of 81,124 remaining unique tweets (52,303-Biden, 28,821-Ryan).

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Presidential Candidate Sentiment Analysis

October 7, 2012
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Presidential Candidate Sentiment Analysis

After watching the Presidential debates and hearing all the opinions on how the candidates performed, I got the hair brained idea of creating a simple function that would do automate the pulling down of tweets for each candidate, analyze the positivity or negativity of tweets, and then graph them out. This project turned out to

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Querying a database from within R

August 18, 2012
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Querying a database from within R

For a while now I have been contemplating pulling data from our postgreSQL db directly from R, but just never actually pulled the trigger until today.  What I found was that it was a lot easier than I ever could have imagined.  My laptop was already on the VPN, so I decided to try it

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Fun with geocoding and mapping in JGR

July 31, 2012
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Fun with geocoding and mapping in JGR

For a recent project I had to do some mapping of addresses, but I didn’t have there lat/lons do use the Deducer and DeducerSpatial packages in R JGR.  After frustrating myself trying to adapt this code from stackoverflow.com, I found a much easier way of geocoding using the dismo and XML packages in R. First

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Converting cross sectional data with dates to weekly averages in R.

May 30, 2012
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Converting cross sectional data with dates to weekly averages in R.

I was recently confronted with a problem where I had to compare two very different data sets. The problem was that one data set was observed cross sectional data with dates over the course of three months and the other was weekly averages during those same three months.  After a bit of research, I discovered

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