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      Impact of Rumors and Misinformation on COVID-19 in Social Media

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          Abstract

          The coronavirus disease 2019 (COVID-19) pandemic has not only caused significant challenges for health systems all over the globe but also fueled the surge of numerous rumors, hoaxes, and misinformation, regarding the etiology, outcomes, prevention, and cure of the disease. Such spread of misinformation is masking healthy behaviors and promoting erroneous practices that increase the spread of the virus and ultimately result in poor physical and mental health outcomes among individuals. Myriad incidents of mishaps caused by these rumors have been reported globally. To address this issue, the frontline healthcare providers should be equipped with the most recent research findings and accurate information. The mass media, healthcare organization, community-based organizations, and other important stakeholders should build strategic partnerships and launch common platforms for disseminating authentic public health messages. Also, advanced technologies like natural language processing or data mining approaches should be applied in the detection and removal of online content with no scientific basis from all social media platforms. Furthermore, these practices should be controlled with regulatory and law enforcement measures alongside ensuring telemedicine-based services providing accurate information on COVID-19.

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          Fake News Detection on Social Media

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            The Effects of Media Reports on Disease Spread and Important Public Health Measurements

            Controlling the spread of influenza to reduce the effects of infection on a population is an important mandate of public health. Mass media reports on an epidemic or pandemic can provide important information to the public, and in turn, can induce positive healthy behaviour practices (i.e., handwashing, social distancing) in the individuals, that will reduce the probability of contracting the disease. Mass media fatigue, however, can dampen these effects. Mathematical models can be used to study the effects of mass media reports on epidemic/pandemic outcomes. In this study we employ a stochastic agent based model to provide a quantification of mass media reports on the variability in important public health measurements. We also include mass media report data compiled by the Global Public Health Intelligence Network, to study the effects of mass media reports in the 2009 H1N1 pandemic. We find that the report rate and the rate at which individuals relax their healthy behaviours (media fatigue) greatly affect the variability in important public health measurements. When the mass media reporting data is included in the model, two peaks of infection result.
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              Fake news detection on social media: A data mining perspective

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                Author and article information

                Journal
                J Prev Med Public Health
                J Prev Med Public Health
                JPMPH
                Journal of Preventive Medicine and Public Health
                Korean Society for Preventive Medicine
                1975-8375
                2233-4521
                May 2020
                2 April 2020
                : 53
                : 3
                : 171-174
                Affiliations
                [1 ]Department of Health Promotion and Community Health Sciences, Texas A&M School of Public Health, College Station, TX, USA
                [2 ]Save the Children, Dhaka, Bangladesh
                Author notes
                Corresponding author: Samia Tasnim, MD Department of Health Promotion and Community Health Sciences, Texas A&M School of Public Health, 212 Adriance Lab Road, College Station, TX 77843, USA E-mail: tasnim@ 123456tamu.edu
                Author information
                http://orcid.org/0000-0002-2686-1840
                http://orcid.org/0000-0002-7059-7768
                http://orcid.org/0000-0003-3787-3780
                Article
                jpmph-53-3-171
                10.3961/jpmph.20.094
                7280809
                32498140
                9a155f6a-8a72-447a-88c9-c406b52283b7
                Copyright © 2020 The Korean Society for Preventive Medicine

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 28 March 2020
                : 2 April 2020
                Categories
                Perspective

                Public health
                covid-19,misinformation,health impacts,social media
                Public health
                covid-19, misinformation, health impacts, social media

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