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Spatial, temporal, and content analysis of Twitter for wildfire hazards

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Listed:
  • Zheye Wang

    (Kent State University)

  • Xinyue Ye

    (Kent State University)

  • Ming-Hsiang Tsou

    (San Diego State University)

Abstract

Social media data are increasingly being used for enhancing situational awareness and assisting disaster management. We analyzed the wildfire-related Twitter activities in terms of their attributes pertinent to space, time, content, and network, so as to gain insights into the usefulness of social media data in revealing situational awareness. Findings show that social media data can characterize the wildfire across space and over time, and thus are applicable to provide useful information on disaster situations. Second, people have strong geographical awareness during wildfire hazards and are interested in communicating situational updates related to wildfire damage (e.g., containment percentage and burned acres), wildfire response (e.g., evacuation), and appreciation to firefighters. Third, news media and local authorities are opinion leaders and play a dominant role in the wildfire retweet network.

Suggested Citation

  • Zheye Wang & Xinyue Ye & Ming-Hsiang Tsou, 2016. "Spatial, temporal, and content analysis of Twitter for wildfire hazards," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 523-540, August.
    • Handle: RePEc:spr:nathaz:v:83:y:2016:i:1:d:10.1007_s11069-016-2329-6
    DOI: 10.1007/s11069-016-2329-6
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    8. Rachel Samuels & John E. Taylor & Neda Mohammadi, 2020. "Silence of the Tweets: incorporating social media activity drop-offs into crisis detection," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 1455-1477, August.
    9. Meng Cai & Han Luo & Xiao Meng & Ying Cui & Wei Wang, 2022. "Influence of information attributes on information dissemination in public health emergencies," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-22, December.
    10. Yan Wang & John E. Taylor, 2018. "Coupling sentiment and human mobility in natural disasters: a Twitter-based study of the 2014 South Napa Earthquake," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(2), pages 907-925, June.
    11. Bianca E. Lopez & Nicholas R. Magliocca & Andrew T. Crooks, 2019. "Challenges and Opportunities of Social Media Data for Socio-Environmental Systems Research," Land, MDPI, vol. 8(7), pages 1-18, July.
    12. Matteo Iacopini & Carlo Romano Marcello Alessandro Santagiustina, 2021. "Filtering the Intensity of Public Concern from Social Media Count Data with Jumps," Post-Print hal-04494229, HAL.
    13. Gabrielle Turner-McGrievy & Amir Karami & Courtney Monroe & Heather M. Brandt, 2020. "Dietary pattern recognition on Twitter: a case example of before, during, and after four natural disasters," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(1), pages 1035-1049, August.
    14. Martínez-Rojas, María & Pardo-Ferreira, María del Carmen & Rubio-Romero, Juan Carlos, 2018. "Twitter as a tool for the management and analysis of emergency situations: A systematic literature review," International Journal of Information Management, Elsevier, vol. 43(C), pages 196-208.
    15. Zhaohui Chong & Chenglin Qin & Xinyue Ye, 2017. "Environmental Regulation and Industrial Structure Change in China: Integrating Spatial and Social Network Analysis," Sustainability, MDPI, vol. 9(8), pages 1-16, August.

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