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Photo of Sean Goggins and Ian Graves.

Sean Goggins, assistant professor in the MU School of Information Science and Learning Technologies (at left), and computer science doctoral student Ian Graves have developed an event-based Twitter analyzation software program.

Computer science doctoral student Ian Graves and Sean Goggins, an assistant professor in the MU School of Information Science and Learning Technologies, paired up to develop an event-based Twitter analyzation software program that is more accurate than existing tools.

Current Twitter analytic tools show the quantity of tweets associated with an event, but these raw numbers don’t give any information about the context of the tweets. Graves’ tool can discover more nuanced information about events, such as the Super Bowl or the World Series, by searching for low-volume, localized tweets and analyzing where certain words occurred in the tweets.

The software Graves developed takes a more qualitative approach to tweet analysis, instead of the traditional quantitative analysis. The tool is able to find the signal in the noise by looking past the sea of hashtags and high volume keywords and searching for other specific words that better analyze the context of the tweets. This analytic method has a variety of practical uses, from community safety and disaster relief to breaking down the cause of events such as the Boston Marathon Bombing.