How do eyewitness social media reports reflect socio-economic effects of natural hazards?

Nataliya Tkachenko*, Rob Procter, Stephen Jarvis

*Corresponding author for this work

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

Abstract

Recent years have seen a remarkable proliferation of studies attempting to establish relationships between observable online human behaviour and various types of crisis (social, political, economic and natural). Methods utilizing user generated content (UGC) have been already applied to various environmental hazards, such as floods, wildfires, earthquakes, tsunamis and other kinds of emergencies. However, what is currently lacking are more detailed insights into differences between the ways people use social media to report various natural hazard events. In this study we make use of the YFCC100M dataset in order to verify whether statistically robust relationships exist between the volumes of uploaded content during different natural hazards and estimated human and economic losses in the affected countries. Our findings demonstrate that Flickr reflect impacts of events with the highest frequency of occurrence (such as floods or storms) and/or with the recurring spatial structure (such as landslides or earthquakes).

Original languageEnglish
Title of host publicationSocial Informatics - 9th International Conference, SocInfo 2017, Proceedings
EditorsGiovanni Luca Ciampaglia, Taha Yasseri, Afra Mashhadi
PublisherSpringer Verlag
Pages221-229
Number of pages9
ISBN (Print)9783319672557
DOIs
Publication statusPublished - 2017
Event9th International Conference on Social Informatics, SocInfo 2017 - Oxford, United Kingdom
Duration: 13 Sept 201715 Sept 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10540 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Social Informatics, SocInfo 2017
Country/TerritoryUnited Kingdom
CityOxford
Period13/09/1715/09/17

Bibliographical note

Publisher Copyright:
© 2017, Springer International Publishing AG.

Keywords

  • Data mining
  • Eyewitness media
  • Flickr
  • Hazard analytics
  • Socio-economics

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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