Assessing the risks of ‘infodemics’ in response to COVID-19 epidemics

Gallotti, Riccardo; Valle, Francesco; Castaldo, Nicola; Sacco, Pier Luigi; Domenico, Manlio De

doi:10.1038/s41562-020-00994-6

Cited by 388 publications

(319 citation statements)

References 46 publications

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“…Figure 5 (a) shows that a first peak in public attention on PPE was reached in late January following the Wuhan lockdown [ 1 ]. A second peak occurred in March [ 84 ] when PPE listings started to appear in DWMs. The number of PPE listings reached their maximum in May.…”

Section: Resultsmentioning

confidence: 99%

“…By revealing that DWMs listings of goods related to COVID-19 exist and are correlated with public attention, we highlight the need for a close monitoring of the online shadow economy in the future months, in order to control and anticipate dangerous effects of the COVID-19 “infodemic” [ 84 , 85 ]. We plan to improve our analysis of DWM activity by increasing the number of monitored DWMs and conducting a more extensive analysis of the impact on the pandemic on overall DWM trade by considering changes in prices of non-COVID-19 specific listings, such as drugs, weapons, or malware.…”

Section: Resultsmentioning

confidence: 99%

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Dark Web Marketplaces and COVID-19: before the vaccine

et al. 2021

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The COVID-19 pandemic has reshaped the demand for goods and services worldwide. The combination of a public health emergency, economic distress, and misinformation-driven panic have pushed customers and vendors towards the shadow economy. In particular, dark web marketplaces (DWMs), commercial websites accessible via free software, have gained significant popularity. Here, we analyse 851,199 listings extracted from 30 DWMs between January 1, 2020 and November 16, 2020. We identify 788 listings directly related to COVID-19 products and monitor the temporal evolution of product categories including Personal Protective Equipment (PPE), medicines (e.g., hydroxyclorochine), and medical frauds. Finally, we compare trends in their temporal evolution with variations in public attention, as measured by Twitter posts and Wikipedia page visits. We reveal how the online shadow economy has evolved during the COVID-19 pandemic and highlight the importance of a continuous monitoring of DWMs, especially now that real vaccines are available and in short supply. We anticipate our analysis will be of interest both to researchers and public agencies focused on the protection of public health.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Dark Web Marketplaces and COVID-19: before the vaccine

et al. 2021

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“…One recent study captures the dissemination of COVID-19 information in relation to the outbreak progression from medical-oriented social media sources [17]. Other studies employing data-driven methodologies have also been introduced to estimate the negative impacts on various sectors such as the economy, public health, and human mobility [18][19][20][21][22][23]. In particular, mobility data have been identified as being especially relevant, and researchers have provided in-depth knowledge on how to leverage mobile device location data for analyzing propagation [24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Human mobility trends during the early stage of the COVID-19 pandemic in the United States

et al. 2020

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In March of this year, COVID-19 was declared a pandemic, and it continues to threaten public health. This global health crisis imposes limitations on daily movements, which have deteriorated every sector in our society. Understanding public reactions to the virus and the non-pharmaceutical interventions should be of great help to fight COVID-19 in a strategic way. We aim to provide tangible evidence of the human mobility trends by comparing the day-by-day variations across the U.S. from January 2020 to early April 2020. Large-scale public mobility at an aggregated level is observed by leveraging mobile device location data and the measures related to social distancing. Our study captures spatial and temporal heterogeneity as well as the sociodemographic variations and teleworking trends regarding the pandemic propagation and the non-pharmaceutical mobility interventions. All metrics adapted capture decreased public movements after the national emergency declaration. The population staying home has increased in all states before the stay-at-home mandates implemented and becomes more stable after the order with a smaller range of fluctuation. The public had been taking active responses, voluntarily staying home more, to the in-state confirmed cases while the stay-at-home orders stabilize the variations. As the estimated teleworking rates also continue to incline throughout the study period, the teleworking trend can be another driving factor for the growing stay-at-home population. We confirm that there exists overall mobility heterogeneity between the income or population density groups. The study suggests that public mobility trends are in line with the government message urging to stay home. We anticipate our data-driven analysis offers integrated perspectives and serves as evidence to raise public awareness and, consequently, reinforce the importance of social distancing while assisting policymakers.

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“…Efforts are devoted to unravel the role played by both humans and software-assisted (i.e., social bots) in disseminating false or inflammatory content for social manipulation, a phenomenon recently discovered during political events (Stella et al 2018), with the ultimate goal of attracting or driving collective attention (Domenico and Altmann 2020) towards a specific information. Products of the individual team members, such as the infodemic observatory model (Gallotti et al 2004) developed by the topic coordinator within the Complex Multilayer Networks Lab at FBK, allow to monitor the current infodemic globally, in each country, or at sub-regional resolution in real time. Information, complemented with the analysis of cognitive content, based on natural language processing and computational psycholinguistics, might help to shed light on mass psychology and socio-behavioral response to the pandemic.…”

Section: Image Analysis (Ct Scans)mentioning

confidence: 99%

The CLAIRE COVID-19 initiative: approach, experiences and recommendations

et al. 2021

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A volunteer effort by Artificial Intelligence (AI) researchers has shown it can deliver significant research outcomes rapidly to help tackle COVID-19. Within two months, CLAIRE's self-organising volunteers delivered the World's first comprehensive curated repository of COVID-19-related datasets useful for drug-repurposing, drafted review papers on the role CT/X-ray scan analysis and robotics could play, and progressed research in other areas. Given the pace required and nature of voluntary efforts, the teams faced a number of challenges. These offer insights in how better to prepare for future volunteer scientific efforts and large scale, data-dependent AI collaborations in general. We offer seven recommendations on how to best leverage such efforts and collaborations in the context of managing future crises.

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Assessing the risks of ‘infodemics’ in response to COVID-19 epidemics

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Cited by 388 publications

References 46 publications

Dark Web Marketplaces and COVID-19: before the vaccine

Dark Web Marketplaces and COVID-19: before the vaccine

Human mobility trends during the early stage of the COVID-19 pandemic in the United States

The CLAIRE COVID-19 initiative: approach, experiences and recommendations

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