Assessing relevance of tweets for risk communication

Liu, Xiaohui; Kar, Bandana; Zhang, Chaoyang; Cochran, David M.

doi:10.1080/17538947.2018.1480670

Assessing relevance of tweets for risk communication

Journal Article · 01 June 2018 · International Journal of Digital Earth

DOI:https://doi.org/10.1080/17538947.2018.1480670· OSTI ID:1471917

^[1]; ^[2]; Zhang, Chaoyang ^[3]; ^[4]

Dalhousie Univ., Halifax, NS (Canada). Resilience Research Centre
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Urban Dynamics Inst., Computational Sciences and Engineering Division
Univ. of Southern Mississippi, Hattiesburg, MS (United States). School of Computing
Univ. of Southern Mississippi, Hattiesburg, MS (United States). Dept. of Geography and Geology

Although Twitter is used for emergency management activities, the relevance of tweets during a hazard event is still open to debate. Here in this study, six different computational (i.e. Natural Language Processing) and spatiotemporal analytical approaches were implemented to assess the relevance of risk information extracted from tweets obtained during the 2013 Colorado flood event. Primarily, tweets containing information about the flooding events and its impacts were analysed. Examination of the relationships between tweet volume and its content with precipitation amount, damage extent, and official reports revealed that relevant tweets provided information about the event and its impacts rather than any other risk information that public expects to receive via alert messages. However, only 14% of the geo-tagged tweets and only 0.06% of the total fire hose tweets were found to be relevant to the event. By providing insight into the quality of social media data and its usefulness to emergency management activities, this study contributes to the literature on quality of big data. Future research in this area would focus on assessing the reliability of relevant tweets for disaster related situational awareness.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE; National Science Foundation (NSF); US Department of Homeland Security (DHS)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1471917

Journal Information:: International Journal of Digital Earth, Journal Name: International Journal of Digital Earth Journal Issue: 7 Vol. 12; ISSN 1753-8947

Publisher:: Taylor & FrancisCopyright Statement

Country of Publication:: United States

Language:: English

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97 MATHEMATICS AND COMPUTING
Content relevance
Twitter
emergency management
risk communication
spatiotemporal data mining

Assessing relevance of tweets for risk communication

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References (30)

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