Principal Investigator(s): Dr. Dave Shepard
This project uses data mining to explore how Twitter is used during major disasters. For the Nepal Earthquake of 2015, Shepard and Wan are examining “onlooker behavior”: why users tweet about disasters that do not directly affect them. By exploring the motivation of these onlookers, Shepard and Wan hope to better understand what particular disasters attract users’ attention, and how common such reactions are.
For the Great East Japan Earthquake of 2011, on the other hand, they will explore new event detection methods. A large number of algorithms exist for text mining events by looking for surges of important words, but most methods assume that events are short and discrete. Using an archive of 200 million tweets sent in the month following the earthquake, Shepard hopes to develop a text-mining method for breaking down events into smaller components. This could help make algorithms that understand events more like humans do, as a set of related occurrences that can be grouped. Together, Shepard and Wan hope that these methods will provide insights for both individual users and historians into how Twitter users experience major historical events, and how to manage the volume of social media data available to scholars.