A while back I enrolled on a MOOC module on Data Analytics, and one of the first assignments was to perform a sentiment analysis on twitter. This involved getting a developer API key from Twitter, then writing a python script to suck tweets from the mighty twitter firehose. Analysis involved comparison against a sentiment sorted dictionary of terms.
Whilst those skills are obviously useful, for those not willing to learn Python there’s a cracking tool available to analyse tweets with a hashtag:
http://www.csc.ncsu.edu/faculty/healey/tweet_viz/tweet_app/
I found out about it in a tweet from Randy Olsen, who ran it to visualise the sentiment regarding the recent release of Java 8.
#Java 8 officially launched a week ago. Here is the @twitter sentiment analysis #dataviz for it. pic.twitter.com/kpzS2O0rWl
— Randy Olson (@randal_olson) March 26, 2014
I thought I’d have a look at the #Maharauk14 hashtag and follow over the next few months as we progress toward the big event. So far there are 5 tweets using that hashtag.
The sentiment analysis isn’t very useful on so few, but it’s worth a look at the tag cloud now and to compare it to the final result.
To compare approaches I’ve also set up a hashtag archive on GoogleDocs using Martin Hawksey’s template: http://mashe.hawksey.info/2012/01/twitter-archive-tagsv3/ which does require twitter API keys and what not, but is rather good.
