Helping Crisis Responders Find the Informative Needle in the Tweet Haystack
This work addresses the challenge for crisis responders of efficiently finding actionable information in large volumes of social media data during crises, representing an incremental improvement by packaging existing concepts into a practical tool.
The paper tackled the problem of identifying relevant information from social media data for crisis responders by developing an automatic approach that filters messages for informativeness and tags them for actionable data across eight categories. The result is an openly-available tool called Emina that successfully handles this challenge.
Crisis responders are increasingly using social media, data and other digital sources of information to build a situational understanding of a crisis situation in order to design an effective response. However with the increased availability of such data, the challenge of identifying relevant information from it also increases. This paper presents a successful automatic approach to handling this problem. Messages are filtered for informativeness based on a definition of the concept drawn from prior research and crisis response experts. Informative messages are tagged for actionable data -- for example, people in need, threats to rescue efforts, changes in environment, and so on. In all, eight categories of actionability are identified. The two components -- informativeness and actionability classification -- are packaged together as an openly-available tool called Emina (Emergent Informativeness and Actionability).