Measuring Community Resilience During the COVID-19 based on Community Wellbeing and Resource Distribution

Valinejad, Jaber; Guo, Zhen; Cho, Jin-Hee; Chen, Ing-Ray

doi:10.1101/2022.05.23.22275454

Cited by 4 publications

(2 citation statements)

References 43 publications

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“…Twitter is one of the major community social media platforms. In this regard, numerous studies have employed tweeter to evaluate population behavior [6][7][8][9][10] . Unfortunately, fake news may negatively impact maintaining community wellbeing and equitable resource distribution during COVID-19.…”

Section: Motivationmentioning

confidence: 99%

“…Real news politics (87), medical (29), fauxtography (17), entertainment (13), business (12), viral (5), phenomena (5), crime (5), history (5), health (5) Mixed news coronavirus (67), politics (48), health (32), facebook (29), public (19), medical (17), fact (16), checks (16), posts (10), budget (8) Fake news politics (97), medical (39), fauxtography (13), entertainment (9), junk (9), news (9), viral (7), phenomena (7), technology (6), business…”

Section: Source Subject (An Amount Of News)mentioning

confidence: 99%

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Measuring Community Resilience During the COVID-19 Based on Community Wellbeing and Resource Distribution

et al. 2022

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The COVID-19 pandemic has severely harmed every aspect of our daily lives, resulting in a slew of social problems. Therefore, it is critical to accurately assess the current state of community functionality and resilience under this pandemic for successful recovery. To this end, various types of social sensing tools, such as tweeting and publicly released news, have been employed to understand individuals' and communities' thoughts, behaviors, and attitudes during the COVID-19 pandemic. However, some portions of the released news are fake and can easily mislead the community to respond improperly to disasters like COVID-19. This paper aims to assess the correlation between various news and tweets collected during the COVID-19 pandemic on community functionality and resilience. We use fact-checking organizations to classify news as real, mixed, or fake, and machine learning algorithms to classify tweets as real or fake to measure and compare community resilience (CR). Based on the news articles and tweets collected, we quantify CR based on two key factors, community wellbeing and resource distribution, where resource distribution is assessed by the level of economic resilience and community capital. Based on the estimates of these two factors, we quantify CR from both news articles and tweets and analyze the extent to which CR measured from the news articles can reflect the actual state of CR measured from tweets. To improve the operationalization and sociological significance of this work, we use dimension reduction techniques to integrate the dimensions.

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Section: Motivationmentioning

confidence: 99%

Section: Source Subject (An Amount Of News)mentioning

confidence: 99%

Measuring Community Resilience During the COVID-19 Based on Community Wellbeing and Resource Distribution

et al. 2022

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Multi-Agent Based Stochastic Dynamical Model to Measure Community Resilience

2022

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Emergency services and utilities need appropriate planning tools to analyze and improve infrastructure and community resilience to disasters. Recognized as a key metric of community resilience is the social well-being of a community during a disaster, which is made up of mental and physical social health.Other factors influencing community resilience directly or indirectly are emotional health, emergency services, and the availability of critical infrastructures services, such as food, agriculture, water, transportation, electric power, and communications system. It turns out that in computational social science literature dealing with community resilience, the role of these critical infrastructures along with some important social characteristics is not considered. To address these weaknesses, we develop a new multi-agent based stochastic dynamical model, standardized by overview, design concepts, details, and decision (ODD+D) protocol and derived from neuro-science, psychological and social sciences, to measure community resilience in terms of mental and physical well-being. Using this model, we analyze the micro-macro level dependence between the emergency services and power systems and social characteristics such as fear, risk perception, informationseeking behaviour, cooperation, flexibility, empathy, and experience, in an artificial society. Furthermore, we simulate this model in two case studies and show that a high level of flexibility, experience, and cooperation enhances community resilience. Implications for both theory and practice are discussed.

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Сутність Та Складові Резильєнтності Громад В Контексті Covid-19

Pakhnenko¹

2022

Економіка та суспільство

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У статті здійснено систематизацію підходів до дефініції резильєнтності громади, визначені її специфічні риси та ідентифіковані основні складові формування резильєнтності громади в умовах пандемії COVID-19. Виокремлено 4 основні аспекти розгляду категорії «резильєнтність громади», а саме як атрибуту громади; як процесу зміни стану громади; як адаптації, збереження стійкого стану громади; та як зміцнення і розвитку у відповідь на фактор ризику. Визначені специфічні риси резильєнтності громади, а саме: 1) фактори ризику можуть мати як зовнішнє, так і внутрішнє походження; 2) громада характеризується визначеними географічними межами, соціальним та політичним устроєм; 3) рівень резильєнтності громади позначається на резильєнтності її мешканців, рівні і якості їх життя. Розглянуто етапи теоретичної моделі резильєнтності громади, ідентифіковано основні складові резильєнтності громади, до яких віднесено соціальний капітал, економічний розвиток, людський капітал, фізичні ресурси, а також географічне положення, та розглянуто зазначені складові у призмі пандемії COVID-19.

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Measuring Community Resilience During the COVID-19 based on Community Wellbeing and Resource Distribution

Cited by 4 publications

References 43 publications

Measuring Community Resilience During the COVID-19 Based on Community Wellbeing and Resource Distribution

Measuring Community Resilience During the COVID-19 Based on Community Wellbeing and Resource Distribution

Multi-Agent Based Stochastic Dynamical Model to Measure Community Resilience

Сутність Та Складові Резильєнтності Громад В Контексті Covid-19

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