Fathi, Ramian and Fiedrich, Frank (2022) Social Media Analytics by Virtual Operations Support Teams in disaster management: Situational awareness and actionable information for decision-makers. Frontiers in Earth Science, 10. ISSN 2296-6463
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Abstract
Virtual Operations Support Teams are groups of institutionalized digital volunteers in the field of disaster management who conduct Social Media Analytics tasks for decision-makers in Emergency Operation Centers (EOCs) during hazard situations such as floods. Through interagency integration into EOC structures, the volunteers provide analytical support using advanced tools and monitoring various social media platforms. The goal of VOSTs is to increase decision-makers’ situational awareness through need-oriented analysis and to improve decision-making by providing actionable information in a time-critical work context. In this case study, the data collected during the 2021 flood in Wuppertal, Germany by 22 VOST analysts was processed and analyzed. It was found that information from eight social media platforms could be classified into 23 distinct categories. The analysts’ prioritizations indicate differences in the formats of information and platforms. Disaster-related posts that pose a threat to the affected population’s health and safety (e.g., requests for help or false information) were more commonly prioritized than other posts. Image-heavy content was also rated higher than text-heavy data. A subsequent survey of EOC decision-makers examined the impact of VOST information on situational awareness during this flood. It also asked how actionable information impacted decisions. We found that VOST information contributes to expanded situational awareness of decision-makers and ensures people-centered risk and crisis communication. Based on the results from this case study, we discuss the need for future research in the area of integrating VOST analysts in decision-making processes in the field of time-critical disaster management.
Item Type: | Article |
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Subjects: | STM Library Press > Geological Science |
Depositing User: | Unnamed user with email support@stmlibrarypress.com |
Date Deposited: | 27 Feb 2023 07:54 |
Last Modified: | 20 Jun 2024 13:17 |
URI: | http://journal.scienceopenlibraries.com/id/eprint/607 |