The Analysis of Information Crowdsourcing Cloud for Disaster Management: Case Studies of Taiwan Morakot Typhoon

Wang, Ryan Sheng-Ming

doi:10.22323/1.210.0015

Cited by 2 publications

(1 citation statement)

References 15 publications

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“…These individuals started sending messages to a local government official's social PAQ Vol 46 Issue 4 media account to seek help and information (Chen, 2014). Eventually, the government official responded and used social media to collect and distribute disaster-related information in addition to traditional communication channels (Wang, 2015). After Typhoon Morakot, some local governments started developing websites to organize relief supplies donations and coordinate volunteers during major disaster events (Tainan City Government, 2013).…”

Section: Use Of Icts In Previous Extreme Eventsmentioning

confidence: 99%

Managing Risk in Dynamic Conditions: Emerging Crises, Changing Technologies, and the Collective Capacity to Learn

Comfort¹,

Wang²

2022

Public Administration Quarterly

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Governing unexpected, extreme events requires a fundamental change in the design of planning processes and responsibilities to enable communities to manage novel risks in sustainable ways. The challenge is to create continuous learning processes for communities that include participants at diverse levels of knowledge, skill, vulnerability, and commitment to reducing risk not only for themselves, but for the whole community. To investigate the problem of collective learning under stress, we analyzed processes of organizational learning in the operational context of Taiwan over a series of extreme events, 1999-2020. While collective learning did occur in Taiwan, it is not clear that sustainable management of novel risks has been achieved. Finding the balance between social coherence and system control likely needs to be recalibrated for each new event.

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Section: Use Of Icts In Previous Extreme Eventsmentioning

confidence: 99%

Managing Risk in Dynamic Conditions: Emerging Crises, Changing Technologies, and the Collective Capacity to Learn

Comfort¹,

Wang²

2022

Public Administration Quarterly

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Social Media–Detected Early Disaster Events: An E-Warning System of Emergency Medical Operation Centers Deployed in Taiwan (Preprint)

Chen¹,

Hong²,

Teng³

et al. 2021

Preprint

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BACKGROUND Because messages are broadcast on social media timelessly and efficiently, it is a critical disaster management survey tool. Taiwan’s Regional Emergency Medical Operation Center (REMOC), supervised by the Ministry of Health and Welfare of Taiwan (MOHW), has responded to nationwide disaster messages in real time since 2005. OBJECTIVE To construct an early warning system to reduce the time delay between the outbreak of accidents and messages received by REMOC. METHODS We developed a program to harvest online messages from numerous social media platforms. Messages containing disaster-relevant keywords, such as typhoon, flooding, and traffic accidents, were scrutinized. We applied text analytics methods and an open-source classification tool LibShortText, a support vector machine (SVM) approach, to identify disaster-related messages. REMOC’s on-duty staff used this information system to harvest disaster-related messages and cases between January 2019 and December 2019. The frequency of events and the percentage of the number of messages that were posted faster than the number of messages that were shared were calculated according to the messages shared by traditional media or posted by individual social media users. The engagement rate (ER) was applied to infer the response rate of registered messages by either traditional media or social media users. RESULTS The system filtered 3022 disaster-related messages from 66 588 total messages. The majority of the messages were related to earthquakes (23%), followed by traffic accidents (17%), fires (12%), and floods (3%). A total of 702 messages were related to 142 earthquake episodes. Of them, 35 messages were shared by social media users regarding 18 earthquakes, and 667 messages from traditional media concerned 124 earthquakes. Social media users posted 100% of the messages faster than traditional media reported them (the “early dissemination efficacy” by social media; 124/124). A total of 367 messages regarded 251 fires; social media users shared 122 messages regarding 82 fires, and traditional media posted 245 messages about 169 fires. The early dissemination efficacy of social media for fires was 0.57 hours. A total of 117 messages from 32 floods were harvested, 55 messages about 16 floods were shared by social media users, and 62 messages for 16 floods were posted by traditional media users; the early dissemination efficacy of social media regarding floods was 0.65 hours. CONCLUSIONS Our results indicate that social media users responded to disaster news faster than did traditional media, especially regarding earthquakes, fires, and floods. Of all disasters, earthquakes and floods had the greatest response rate from social media users. The combined usage of REMOCs and social media crawler system could considerably improve the preparation for and the response to natural disasters, particularly earthquakes and floods.

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The Analysis of Information Crowdsourcing Cloud for Disaster Management: Case Studies of Taiwan Morakot Typhoon

Cited by 2 publications

References 15 publications

Managing Risk in Dynamic Conditions: Emerging Crises, Changing Technologies, and the Collective Capacity to Learn

Managing Risk in Dynamic Conditions: Emerging Crises, Changing Technologies, and the Collective Capacity to Learn

Social Media–Detected Early Disaster Events: An E-Warning System of Emergency Medical Operation Centers Deployed in Taiwan (Preprint)

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