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Institutional vs. Non-institutional use of Social Media during Emergency Response: A Case of Twitter in 2014 Australian Bush Fire

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  • Babak Abedin

    (University of Technology Sydney)

  • Abdul Babar

    (University of Sydney)

Abstract

Social media plays a significant role in rapid propagation of information when disasters occur. Among the four phases of disaster management life cycle: prevention, preparedness, response, and recovery, this paper focuses on the use of social media during the response phase. It empirically examines the use of microblogging platforms by Emergency Response Organisations (EROs) during extreme natural events, and distinguishes the use of Twitter by EROs from digital volunteers during a fire hazard occurred in Australia state of Victoria in early February 2014. We analysed 7982 tweets on this event. While traditionally theories such as World System Theory and Institutional Theory focus on the role of powerful institutional information outlets, we found that platforms like Twitter challenge such notion by sharing the power between large institutional (e.g. EROs) and smaller non-institutional players (e.g. digital volunteers) in the dissemination of disaster information. Our results highlight that both large EROs and individual digital volunteers proactively used Twitter to disseminate and distribute fire related information. We also found that the contents of tweets were more informative than directive, and that while the total number of messages posted by top EROs was higher than the non-institutional ones, non-institutions presented a greater number of retweets.

Suggested Citation

  • Babak Abedin & Abdul Babar, 2018. "Institutional vs. Non-institutional use of Social Media during Emergency Response: A Case of Twitter in 2014 Australian Bush Fire," Information Systems Frontiers, Springer, vol. 20(4), pages 729-740, August.
    • Handle: RePEc:spr:infosf:v:20:y:2018:i:4:d:10.1007_s10796-017-9789-4
    DOI: 10.1007/s10796-017-9789-4
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    References listed on IDEAS

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    1. Jaeung Lee & Manish Agrawal & H. R. Rao, 2015. "Message diffusion through social network service: The case of rumor and non-rumor related tweets during Boston bombing 2013," Information Systems Frontiers, Springer, vol. 17(5), pages 997-1005, October.
    2. Butts, Carter T., 2008. "Social Network Analysis with sna," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i06).
    3. Seyedezahra Shadi Erfani & Babak Abedin & Yvette Blount, 2017. "The effect of social network site use on the psychological well-being of cancer patients," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(5), pages 1308-1322, May.
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    1. Kerstin K. Zander & Jonas Rieskamp & Milad Mirbabaie & Mamoun Alazab & Duy Nguyen, 2023. "Responses to heat waves: what can Twitter data tell us?," 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. 116(3), pages 3547-3564, April.
    2. Ghassan Beydoun & Sergiu Dascalu & Dale Dominey-Howes & Andrew Sheehan, 2018. "Disaster Management and Information Systems: Insights to Emerging Challenges," Information Systems Frontiers, Springer, vol. 20(4), pages 649-652, August.
    3. Fatuma Namisango & Kyeong Kang & Ghassan Beydoun, 2022. "How the Structures Provided by Social Media Enable Collaborative Outcomes: A Study of Service Co-creation in Nonprofits," Information Systems Frontiers, Springer, vol. 24(2), pages 517-535, April.
    4. Emily Heaney & Laura Hunter & Angus Clulow & Devin Bowles & Sotiris Vardoulakis, 2021. "Efficacy of Communication Techniques and Health Outcomes of Bushfire Smoke Exposure: A Scoping Review," IJERPH, MDPI, vol. 18(20), pages 1-14, October.
    5. Yanxin Wang & Jian Li & Xi Zhao & Gengzhong Feng & Xin (Robert) Luo, 2020. "Using Mobile Phone Data for Emergency Management: a Systematic Literature Review," Information Systems Frontiers, Springer, vol. 22(6), pages 1539-1559, December.
    6. Ghassan Beydoun & Babak Abedin & José M. Merigó & Melanie Vera, 2019. "Twenty Years of Information Systems Frontiers," Information Systems Frontiers, Springer, vol. 21(2), pages 485-494, April.
    7. Naim Kapucu & Ratna B Dougherty & Yue Ge & Chris Zobel, 2023. "The use of documentary data for network analysis in emergency and crisis management," 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. 116(1), pages 425-445, March.
    8. Carine Dominguez-Péry & Rana Tassabehji & Lakshmi Narasimha Raju Vuddaraju & Vikhram Kofi Duffour, 2021. "Improving emergency response operations in maritime accidents using social media with big data analytics: a case study of the MV Wakashio disaster," Post-Print hal-04021179, HAL.
    9. Qingqi Long & Ke Song, 2022. "Operational Performance Evaluation of E-government Microblogs Under Emergencies Based on a DEA Method," Information Systems Frontiers, Springer, vol. 24(5), pages 1-18, October.
    10. Jyoti Prakash Singh & Abhinav Kumar & Nripendra P. Rana & Yogesh K. Dwivedi, 2022. "Attention-Based LSTM Network for Rumor Veracity Estimation of Tweets," Information Systems Frontiers, Springer, vol. 24(2), pages 459-474, April.
    11. Paras Bhatt & Naga Vemprala & Rohit Valecha & Govind Hariharan & H. Raghav Rao, 2023. "User Privacy, Surveillance and Public Health during COVID-19 – An Examination of Twitterverse," Information Systems Frontiers, Springer, vol. 25(5), pages 1667-1682, October.
    12. Shalak Mendon & Pankaj Dutta & Abhishek Behl & Stefan Lessmann, 2021. "A Hybrid Approach of Machine Learning and Lexicons to Sentiment Analysis: Enhanced Insights from Twitter Data of Natural Disasters," Information Systems Frontiers, Springer, vol. 23(5), pages 1145-1168, September.
    13. Josip Marić & Carlos Galera-Zarco & Marco Opazo-Basáez, 2022. "The emergent role of digital technologies in the context of humanitarian supply chains: a systematic literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1003-1044, December.
    14. Franco Arolfo & Kevin Cortés Rodriguez & Alejandro Vaisman, 2022. "Analyzing the Quality of Twitter Data Streams," Information Systems Frontiers, Springer, vol. 24(1), pages 349-369, February.
    15. Ziqiang Han & Mengfan Shen & Hongbing Liu & Yifan Peng, 2022. "Topical and emotional expressions regarding extreme weather disasters on social media: a comparison of posts from official media and the public," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-10, December.

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