Identifying Panic Triggers from Disaster-Related Tweets

Assery, Nasser; Yuan, Xiaojun; Qu, Xiuli; Almalki, Sultan

doi:10.1109/ispa-bdcloud-socialcom-sustaincom51426.2020.00129

Cited by 3 publications

(1 citation statement)

References 30 publications

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“…Many studies highlight the usefulness of technologies for EDMPP. To focus on a few technologies; various studies describe the utility of artificial intelligence and machine learning and reasoning [69,71,80,168,169,[193][194][195][196][197][198][199][200][201][202][203][204][205][206][207][208][209][210] for EDMPP including for the evaluation of societal implications [211]. If it is seen as useful to evaluate societal implications, the data must contain high quality information on the 'social', especially in relation to marginalized groups.…”

Section: Edmpp Marginalized Groups Edi and Technologymentioning

confidence: 99%

Emergency and Disaster Management, Preparedness, and Planning (EDMPP) and the ‘Social’: A Scoping Review

Lillywhite

Wolbring

2022

Sustainability

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The importance of emergency and disaster management, preparedness, and planning (EDMPP) is ever increasing with COVID-19 being one recent EDMPP challenge. EDMPP is impacted by and impacts the ‘social’ of individuals and societies. Therefore, a thorough understanding of the ‘social’ is important for providing EDMPP. Marginalized populations are over-proportionally impacted by emergencies and disasters and often overlooked in EDMPP. Therefore, it is especially important to understand the lived experience of marginalized groups and to involve marginalized groups in providing knowledge for EDMPP. Technologies such as artificial intelligence and machine learning and reasoning, e-coaching, other decision support systems and Bayesian belief networks are increasingly employed for EDMPP. However, biases and other problems in the use of technologies for EDMPP are noted. Understanding the ‘social’ of marginalized populations and others is essential for designing algorithms and other technologies that are not biased towards marginalized populations and others. The phrase “equity, diversity, and inclusion” (EDI), other EDI linked phrases, and EDI frameworks are increasingly employed in workplaces to improve research, education, and workplace environments for marginalized groups such as women, Indigenous Peoples, visible minorities, racialized minorities, disabled people, people with disabilities and LGBTQ2S+. EDMPP actors are workers. Using EDI in EDMPP could improve the EDMPP situation of marginalized groups by encouraging knowledge production by and about marginalized groups related to EDMPP. The main objective of this study was to map out the engagement with the ‘social’, EDI and marginalized groups in the EDMPP-focused academic literature in general and the EDMPP academic literature covering disabled people, patients, technologies and COVID-19. A scoping review using the academic databases SCOPUS, Web of Science, and the databases accessible under Compendex and EBSCO-HOST were employed to fulfill the objectives. The study found little coverage of marginalized populations and EDI phrases and frameworks, and a lack of many terms linked to the ‘social’ in the literature searched. These gaps need to be filled given the importance of EDMPP to the ‘social’ of individuals and societies.

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Section: Edmpp Marginalized Groups Edi and Technologymentioning

confidence: 99%

Emergency and Disaster Management, Preparedness, and Planning (EDMPP) and the ‘Social’: A Scoping Review

Lillywhite

Wolbring

2022

Sustainability

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Surveying the Use of Social Media Data and Natural Language Processing Techniques to Investigate Natural Disasters

Ma,

Li,

Mao

et al. 2024

Nat. Hazards Rev.

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Leveraging Disruptive Technologies for Faster and More Efficient Disaster Response Management

Calle Müller,

Lagos,

Elzomor

2024

Sustainability

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Natural disasters cause extensive infrastructure and significant economic losses, hindering sustainable development and impeding social and economic progress. More importantly, they jeopardize community well-being by causing injuries, damaging human health, and resulting in loss of life. Furthermore, communities often experience delayed disaster response. Aggravating the situation, the frequency and impact of disasters have been continuously increasing. Therefore, fast and effective disaster response management is paramount. To achieve this, disaster managers must proactively safeguard communities by developing quick and effective disaster management strategies. Disruptive technologies such as artificial intelligence (AI), machine learning (ML), and robotics and their applications in geospatial analysis, social media, and smartphone applications can significantly contribute to expediting disaster response, improving efficiency, and enhancing safety. However, despite their significant potential, limited research has examined how these technologies can be utilized for disaster response in low-income communities. The goal of this research is to explore which technologies can be effectively leveraged to improve disaster response, with a focus on low-income communities. To this end, this research conducted a comprehensive review of existing literature on disruptive technologies, using Covidence to simplify the systematic review process and NVivo 14 to synthesize findings.

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Identifying Panic Triggers from Disaster-Related Tweets

Cited by 3 publications

References 30 publications

Emergency and Disaster Management, Preparedness, and Planning (EDMPP) and the ‘Social’: A Scoping Review

Emergency and Disaster Management, Preparedness, and Planning (EDMPP) and the ‘Social’: A Scoping Review

Surveying the Use of Social Media Data and Natural Language Processing Techniques to Investigate Natural Disasters

Leveraging Disruptive Technologies for Faster and More Efficient Disaster Response Management

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