Bots and Misinformation Spread on Social Media: Implications for COVID-19 (Preprint)

Himelein-Wachowiak, McKenzie; Giorgi, Salvatore; Devoto, Amanda; Rahman, Muhammad Mahbubur; Ungar, Lyle; Schwartz, H. Andrew; Epstein, David H.; Leggio, Lorenzo; Curtis, Brenda

doi:10.2196/preprints.26933

Cited by 15 publications

(1 citation statement)

References 79 publications

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“…A study conducted by (9) stated that, the origin of SARS-CoV-2 is still a mystery even though it is established that it is a zoonotic virus. In December 2019, a 55 years old individual was the rst case of COVID-19 that was detected in the Wuhan city of the Hubei province in the People's Republic of China (15).…”

Section: Background Of the Studymentioning

confidence: 99%

Knowledge and Practices Regarding the Prevention Principles of Covid-19 Among Third Year Degree Nursing Students at a University Khomas Region, Namibia

Nyanya

Kadhila

2022

Preprint

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Background:The rapid spread of SARS-CoV-2 is responsible for the global pandemic. Since the outbreak of COVID-12 began, necessary measurements and policies were provided to the public for prevention of the transmission of the disease. This measures and polies included: mandatory wearing of a mask in public, social distancing, regular hand sanitizing, and avoidance of overcrowded places etc. This study assessed the knowledge and practices regarding the prevention principles of covid-19 among third year degree nursing students at a University Khomas region, Namibia. Methods: A quantitative study was conducted on 77 study population and participants who were chosen using simple random sampling. The data was collected with the use of questionnaires. A pilot study was done on 5 participants to assess reliability of the data collection tool/questionnaire, or if there would be any changes that have to be made in the questionnaires and to note down time spent on answering the questionnaires. Data was analyzed with Microsoft excel version and descriptive analysis. The findings are presented in pie charts, bar graph and tables. Results:The findings showed that, most of the students 91% have good knowledge and practices regarding the prevention principles of OVID-19. Although the findings indicated overall good knowledge and good practices regarding applications of the preventive principles for COVID-19, the findings nevertheless indicated that 71% of the participants had average knowledge, 23,4% had poor knowledge while, 90% had average practices and 32% had poor practice regarding applications of the preventive principles for COVID-19. Out of the 77 participants, only 1% of the student know that COVI-19 is disease and the whole 99% don’t know which, apart from that poor knowledge, 25 participants from the 77, think getting vaccinated will prevent getting infected by COVID-19, but it only reduces getting infected. Conclusion:Some knowledge and practice gaps were identified about the students not having average or poor knowledge whether COVID-19 is a disease or virus and that getting vaccinated prevent one from getting infected or reduce the risk of getting infected. Apart from that, third year nursing degree students have good knowledge and practices on COVID-19 prevents

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Section: Background Of the Studymentioning

confidence: 99%

Knowledge and Practices Regarding the Prevention Principles of Covid-19 Among Third Year Degree Nursing Students at a University Khomas Region, Namibia

Nyanya

Kadhila

2022

Preprint

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Bayesian identification of bots using temporal analysis of tweet storms

Kirn

Hinders

2021

Soc. Netw. Anal. Min.

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FOMO (fate of online media only) in infectious disease modeling: a review of compartmental models

Sooknanan

Seemungal

2022

Int. J. Dynam. Control

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Mathematical models played in a major role in guiding policy decisions during the COVID-19 pandemic. These models while focusing on the spread and containment of the disease, largely ignored the impact of media on the disease transmission. Media plays a major role in shaping opinions, attitudes and perspectives and as the number of people online increases, online media are fast becoming a major source for news and health related information and advice. Consequently, they may influence behavior and in due course disease dynamics. Unlike traditional media, online media are themselves driven and influenced by their users and thus have unique features. The main techniques used to incorporate online media mathematically into compartmental models, with particular reference to the ongoing COVID-19 pandemic are reviewed. In doing so, features specific to online media that have yet to be fully integrated into compartmental models such as misinformation, different time scales with regards to disease transmission and information, time delays, information super spreaders, the predatory nature of online media and other factors are identified together with recommendations for their incorporation.

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Bots and Misinformation Spread on Social Media: Implications for COVID-19 (Preprint)

Cited by 15 publications

References 79 publications

Knowledge and Practices Regarding the Prevention Principles of Covid-19 Among Third Year Degree Nursing Students at a University Khomas Region, Namibia

Knowledge and Practices Regarding the Prevention Principles of Covid-19 Among Third Year Degree Nursing Students at a University Khomas Region, Namibia

Bayesian identification of bots using temporal analysis of tweet storms

FOMO (fate of online media only) in infectious disease modeling: a review of compartmental models

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