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Sentiment analysis of twitter users over time: The case of the Boston bombing tragedy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Social Network Services (SNS), for example Twitter, play a significant role in the way people share their emotions about specific events. Emotions can spread via SNS and can spur people’s future actions. Therefore, during extreme events, disaster response agencies need to manage emotions appropriately via SNS. In this research, we investigate the Twitter verse associated with an event - the Boston Bombing context. We focus on tweets in the context of hazard-describing keywords (Explosion, Bomb), important event timelines, and the related changes in emotions over time. We compare the results with a corpus of tweets collected at the same time that are not associated with the above hazard- describing keywords. A sentiment analysis shows anger was the most strongly expressed emotion in both groups. However, there were statistical differences in Anxiety and Sadness among the two groups over time.

Original languageEnglish
Title of host publicationE-Life
Subtitle of host publicationWeb-Enabled Convergence of Commerce, Work, and Social Life - 15th Workshop on e-Business, WEB 2015, Revised Selected Papers
EditorsVijayan Sugumaran, Victoria Yoon, Michael J. Shaw
PublisherSpringer Verlag
Pages1-14
Number of pages14
ISBN (Print)9783319454078
DOIs
StatePublished - 2016
Event15th Workshop on e-Business on E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life, WEB 2015 - Fort Worth, United States
Duration: Dec 12 2015Dec 12 2015

Publication series

NameLecture Notes in Business Information Processing
Volume258

Conference

Conference15th Workshop on e-Business on E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life, WEB 2015
Country/TerritoryUnited States
CityFort Worth
Period12/12/1512/12/15

Keywords

  • Announcement
  • Big data
  • Disaster response
  • Emotion spread
  • Social media

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