A behavior analytics approach to identifying tweets from crisis regions

Shamanth Kumar, Xia Hu, Huan Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Scopus citations

Abstract

The growing popularity of Twitter as an information medium has allowed unprecedented access to first-hand information during crises and mass emergency situations. Due to the sheer volume of information generated during a disaster, a key challenge is to filter tweets from the crisis region so their analysis can be prioritized. In this paper, we introduce the task of identifying whether a tweet is generated from crisis regions and formulate it as a decision problem. This problem is challenging due to the fact that only ∼1% of all tweets have location information. Existing approaches tackle this problem by predicting the location of the user using historical tweets from users or their social network. As collecting historical information is not practical during emergency situations, we investigate whether it is possible to determine that a tweet originates from the crisis region through the information in the tweet and the publishing user's profile.

Original languageEnglish (US)
Title of host publicationHT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media
PublisherAssociation for Computing Machinery
Pages255-260
Number of pages6
ISBN (Print)9781450329545
DOIs
StatePublished - Jan 1 2014
Event25th ACM Conference on Hypertext and Social Media, HT 2014 - Santiago, Chile
Duration: Sep 1 2014Sep 4 2014

Publication series

NameHT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media

Conference

Conference25th ACM Conference on Hypertext and Social Media, HT 2014
CountryChile
CitySantiago
Period9/1/149/4/14

Keywords

  • crisis tweets
  • situational awareness
  • user behavior in tweets

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Software

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  • Cite this

    Kumar, S., Hu, X., & Liu, H. (2014). A behavior analytics approach to identifying tweets from crisis regions. In HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media (pp. 255-260). (HT 2014 - Proceedings of the 25th ACM Conference on Hypertext and Social Media). Association for Computing Machinery. https://doi.org/10.1145/2631775.2631814