By programming a “bag of words,” or tags they felt would be associated with the Super Bowl and World Series, the software analysed the words and their placement within the 140 character tweets.

“The software is able to detect more nuanced occurrences within the tweet, like action happening on the baseball field in between batters at the plate or plays in the game,” Graves said.

“The programme uses a computational approach to seek out not only a spike in hashtags or words, but also what’s really happening on a micro level. By looking for low—volume, localised tweets, we gleaned intelligence that stood apart from the clutter and noise associated with tweets related to the World Series,” Graves said.

Goggins feels using this method to analyse tweets on a local level can help officials involved with community safety or disaster relief to investigate the causes of major events or to help predict future events.

“Most of the things that happen on Twitter are not related to specific events in the world,” Goggins said.

“If analysts are just looking at the volume of tweets, they’re not getting the insight they need about what’s truly happening or the whole picture. By focusing on the words within the tweet, we have the potential to find a truer signal inside of a very noisy environment,” Goggins said.

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