ABSTRACT
Social media platforms often become environments of information ambiguity during crisis events. We studied the discussion around four”cures” for COVID-19 in India, where the highest number of cases were recorded between 2020 and May 2021, focusing on the role played by high network accounts on social media such as those of journalists, politicians, and celebrities. We find that information scarcity and anxiety among citizens enabled non-experts, particularly the aforementioned social media influencers. We find that this undermined institutional sources of information and led to massive spikes in online interest around unproven cures during the peak of the crisis. © 2022 IEEE Computer Society. All rights reserved.
ABSTRACT
By employing two systemic risk methods, the marginal expected shortfall (MES) and the component expected shortfall (CES), this paper measures the systemic risk level of all sectors in China's financial market from 2014 to 2022;thereby, it researches the total effect of sectoral systemic risk using a panel event study model during the three main emergency crisis events. Moreover, two nonparametric methods are utilized, the Wilcoxon signed rank sum test and the bootstrap Kolmogorov–Smirnov test, in order to investigate the changes in individual effects and the dominant ranks of sectoral systemic risk. The empirical results show that (1) the mean values and volatilities of CES and MES of all sectors have a higher level of magnitude in the extreme risk status than those in the normal risk status;(2) by comparing the total effects of three crisis events, we find that different from the continuous shock effect caused by two other events, sectoral systemic risk has a hysteresis effect on the entire market after the outbreak of COVID-19;(3) the long-term and short-term individual effects of sectoral systemic risk in all sectors are different from each other during three events;and (4) the dominance tests of MES are more sensitive and thus better demonstrate the changes in the rankings of sectoral systemic risk than the dominant tests of CES during the emergency crisis events. © 2023 by the authors.
ABSTRACT
Accurately quantifying industry resilience is essential to devising effective recovery strategies. Previous research into industry resilience has either quantified the concept with single metrics aggregated across large geographies (e.g., visitation) or used metrics comparing the relative concentration of an industry within a region to the national average (e.g., location quotients). The former set of metrics prohibits spatially targeted recovery efforts while the latter fails during national crises. We propose the measurement of tourism and outdoor recreation industry resilience to COVID-19 based on growth rates in employment, wages, and establishments using publicly accessible time-series data on all counties in the United States. We use these indicators to characterize the spatio-temporal patterns of industry resilience across the country. The indicators can serve as a useful reference for diagnosing and monitoring industry resilience as well as developing targeted policies, programs, and promotion efforts that facilitate more localized response efforts. © 2022 Elsevier Ltd
ABSTRACT
The widespread application of social media in the field of crisis management has been adopted globally. In recent years, the role of social media in emergencies has grown, especially during the coronavirus disease 2019 (COVID-19) pandemic. This study explores the different roles played by social media in the government, the media, and the public during the pandemic through the key nodes of information dissemination at each developmental stage of crisis risk communication. The results indicate that in a government-led environment, in which social media is the link and the public is the core, attention must be directed towards the key role of social media as a "whistleblower” during the incubation period of a crisis event. Moreover, a new gatekeeping mechanism that integrates the public, the media, and the government should be formed to improve emergency management during crises. © Fuji Technology Press Ltd.
ABSTRACT
With the surge of deep uncertainties and multi-dimensional impacts of crisis events, social resilience assessment needs to advance the analysis of dynamic influencing process for urban system. To this end, this paper investigates the resilience assessment method of social resilience by using the differences analysis between capacities and demands. A gap analysis-based assessment method for social resilience is developed to quantify the resilience gap and levels, and a systemic resilience analysis framework is proposed to support overall analysis of urban systems. To verify the proposed method, we apply it to the novel coronavirus 2019 (COVID-19) epidemic in Shanghai during the period of February to May, 2022. Based on the data analysis of COVID-19-related cases, we compared the capacities and demands in urban medical system of patients transferring, admission and healing procedure. The fluctuations of resilience levels are examined and discussed. In addition, the resilience analysis of social systems and governance capacity in COVID-19 crisis are further carried out, and three-layer measures and procedure optimizations are introduced to build social resilience. The proposed resilience assessment method and systemic resilience management measures have potential implications and applications in the practical epidemic prevention and control. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Identification of fine-grained location mentions in crisis tweets is central in transforming situational awareness information extracted from social media into actionable information. Most prior works have focused on identifying generic locations, without considering their specific types. To facilitate progress on the fine-grained location identification task, we assemble two English tweet crisis datasets and manually annotate them with specific location types. The first dataset contains tweets from a mixed set of crisis events, while the second dataset contains tweets from the global COVID-19 pandemic. We investigate the performance of state-of-the-art deep learning models for sequence tagging on these datasets, in both in-domain and cross-domain settings. © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.
ABSTRACT
This study crawled the cross-sectional data of the contents and comments from Microblog Account Xiake Island during the outbreak of coronavirus pneumonia as subjects, to examine the deviation and resonance association among affective fluctuations of the Chinese public, media framework, and audiences' cognitive framework. Using SnowNLP to conduct sentiment analysis of text comments, we found that during the outbreak of coronavirus pneumonia, the public spent most of the time in low-intensity negative affectivity, and the average affective propensity in response to individual microblog fluctuated greatly, and the public was easily caught in an emotional frenzy, which reduces the level of trust in government. Through a comparison of public affectivity and related epidemic data, Xiake Island focuses on reporting emotional facts, whose construction of social reality contains obvious emotional trajectories. Clustering analysis of thematic framework by LDA algorithm reveals that in terms of framework, the framework Xiake Island uses resonates to a large degree with the framework users focus on. In terms of the level of concerns over the framework, Xiake Island deviates to a certain extent from the public. This deviation, together with the strategy of focusing on reporting emotional facts, is a discursive strategy adopted by the new mainstream media to seek the reconstruction of cultural leadership. © 2022 Owner/Author.
ABSTRACT
Given the broad scope of Ethereum and the wide range of its decentralized applications, this paper investigates its hedging and safe haven capabilities against main fiat currencies, stock and bond indices in the US and Europe, and crude oil and gold markets. We use daily data from January 2016 until February 2021 and apply percentile regressions and crisis event interaction analysis by selecting four worldwide events including US presidential elections, the Brexit referendum, and COVID-19. We reveal that Ethereum does not act as a hedge or a safe haven against fiat currencies, stock and bond indices, and gold. However, it does act as a strong safe haven against crude oil in calm and turbulent periods and against European bonds during market turbulence. The study provides insights to regulators and investors into the potential role of Ethereum in investment decision-making and protecting financial market participants in the US and EU.
ABSTRACT
Accurately quantifying industry resilience is essential to devising effective recovery strategies. Previous research into industry resilience has either quantified the concept with single metrics aggregated across large geographies (e.g., visitation) or used metrics comparing the relative concentration of an industry within a region to the national average (e.g., location quotients). The former set of metrics prohibits spatially targeted recovery efforts while the latter fails during national crises. We propose the measurement of tourism and outdoor recreation industry resilience to COVID-19 based on growth rates in employment, wages, establishments—publicly accessible time-series data on all counties in the United States. We use these indicators to characterize the spatio-temporal patterns of industry resilience across the country. The indicators can serve as a useful reference for diagnosing and monitoring industry resilience as well as developing targeted policies, programs, and promotion efforts that facilitate more localized response efforts.
ABSTRACT
There has been an increased usage and popularity of digital platforms during the COVID-19 crisis. This has resulted in many new types of digital platforms emerging that are tied to specific localities and based on emergent needs. This article presents the results of a study on the ClickforVic digital platform that was started during the first 2020 lockdown in Melbourne, Australia as a way for country farmers to connect with urban consumers. The study is premised on transformational entrepreneurship theory that enables a focus on the societal changes that have resulted from the COVID-19 pandemic. A semi-structured in-depth interview approach was utilised to understand how farm entrepreneurs perceived the digital platform and how this contributed to transformational entrepreneurship outcomes. The study is amongst the first to incorporate a digital platform, farm entrepreneurship, transformational entrepreneurship and COVID-19 perspective. The findings suggest that farm entrepreneurs are driven by financial, social and community goals during a crisis that influences their usage of digital platforms. As a consequence, the findings contribute to managerial practice and policy debate by highlighting the way digital platforms can be used in times of crisis to produce transformational entrepreneurship outcomes.
ABSTRACT
Organizational resilience plays a significant role for enterprises in dealing with both natural disasters and economic crises. Past studies have examined the possible antecedents of organizational resilience in crisis events. However, the existing research is based on the assumption that each antecedent variable acts independently on the result variable. In this study, fuzzy-set qualitative comparative analysis (fsQCA) method is used to solve this limitation. Based on the background of COVID-19, this study takes 74 small and medium-sized enterprises as samples to explore the mechanism of seven antecedents on organizational resilience from three levels: resources, capacity and system. The results show that multiple asymmetric paths lead to the occurrence of high resilience and non-high resilience. Clarifying this conclusion can guide managers to decide how to allocate resources to improve the resilience of enterprises. © 2021 ACM.
ABSTRACT
In 2020, we have witnessed an unprecedented crisis event, the COVID-19 pandemic. Various questions arise regarding the nature of this crisis data and the impacts it would have on the existing tools. In this paper, we aim to study whether we can include pandemic-type crisis events with general non-pandemic events and hypothesize that including labeled crisis data from a variety of non-pandemic events will improve classification performance over models trained solely on pandemic events. To test our hypothesis we study the model performance for different models by performing a cross validation test on pandemic only held-out sets for two different types of training sets, one containing only pandemic data and the other a combination of pandemic and non-pandemic crisis data, and comparing the results of the two. Our results approve our hypothesis and give evidence of some crucial information propagation upon inclusion of non-pandemic crisis data to pandemic data. © 2021 Information Systems for Crisis Response and Management, ISCRAM. All rights reserved.
ABSTRACT
Crisis Named Resources (CNRs) are social media accounts and pages named after a crisis event. They are created soon after an event occurs. CNRs share a lot of information around an event and are followed by many. In this study, we identify CNRs created around COVID-19 on Facebook, Twitter, and Reddit. We analyze when these resources were created, why they were created, how they were received by members of the public, and who created them. We conclude by comparing CNRs created around COVID-19 with past crisis events and discuss how CNR owners attempt to manage content and combat misinformation. © 2021 Information Systems for Crisis Response and Management, ISCRAM. All rights reserved.
ABSTRACT
Little research has examined the mental health risks of concurrent disasters. For example, disasters like wildfires have been shown to have a strong association with psychological symptoms-the 2020 U.S. Western wildfire season was the worst on record and occurred while the country was still navigating the COVID-19 pandemic. We implemented two quasi-experimental analyses, an interrupted time series analysis, and a difference-in-difference analysis to evaluate the impacts of wildfires and COVID-19 on mental health crisis help-seeking patterns. Both methods showed no statistical association between exposure to wildfires and the seeking of mental health support during the COVID-19 pandemic. Results highlighted that 2020 wildfires were not associated with an acute increase in crisis texts for youth in the two months after the events, likely due to an already elevated text volume in response to the COVID-19 pandemic from March 2020 throughout the fall wildfire season (Aug to Oct 2020). Future research is needed outside of the context of the pandemic to understand the effects of extreme and concurrent climatic events on adolescent mental health, and targeted interventions are required to ensure youth and adolescents are receiving adequate support during these types of crisis events.