As a psychologist scientist, data enthusiast, and novice programmer, one of the things I’ve been really interested in lately is applying text-mining tools to social media to learn more about public opinion on important news stories and current events.

I know it’s cliche to say it, but social media is an incredibly powerful tool. Not only does it obviously allow friends, family, and colleagues to easily communicate and share information with one another in near real-time, but it also provides a rich storehouse of communications for researchers and data geeks, such as myself, to comb thorough and mine for interesting patterns in human behavior and human thought.

For instance, I’ve previously written about research demonstrating how Twitter can be used to predict the risk of dying from a heart attack in particular regions of the country. And more recently, I’ve done a bit of text-mining in Twitter to try to learn more about our President’s tweeting habit, such as the time of day he generally prefers to tweet (usually around 8:00 am EST), the most frequent words he uses when he tweets (“thank,” “great,” and “Hillary”),* and whether his tweets include mostly positive or mostly negative words (on average it’s split pretty evenly, actually).

So, with my political and scientific interests being what they are, I figured I would turn to Twitter to try to learn a little more about how people have perceived and reacted to the continuous flood of news stories that has been coming out of North Carolina recently. Read more “What’s Twitter’s Opinion of North Carolina Politics?”