Why do People Share Misinformation during the COVID-19 Pandemic?

• URL: http://arxiv.org/abs/2004.09600v1
• Date: Mon, 20 Apr 2020 19:56:48 GMT
• Title: Why do People Share Misinformation during the COVID-19 Pandemic?
• Authors: Samuli Laato, A.K.M. Najmul Islam, Muhammad Nazrul Islam and Eoin Whelan
• Abstract summary: We develop and test a research model hypothesizing why people share unverified COVID-19 information through social media. Our findings suggest a person's trust in online information and perceived information overload are strong predictors of unverified information sharing. Females were significantly more likely to suffer from cyberchondria, however, males were more likely to share news without fact checking their source.
• Score: 0.6963971634605797
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The World Health Organization have emphasised that misinformation - spreading rapidly through social media - poses a serious threat to the COVID-19 response. Drawing from theories of health perception and cognitive load, we develop and test a research model hypothesizing why people share unverified COVID-19 information through social media. Our findings suggest a person's trust in online information and perceived information overload are strong predictors of unverified information sharing. Furthermore, these factors, along with a person's perceived COVID-19 severity and vulnerability influence cyberchondria. Females were significantly more likely to suffer from cyberchondria, however, males were more likely to share news without fact checking their source. Our findings suggest that to mitigate the spread of COVID-19 misinformation and cyberchondria, measures should be taken to enhance a healthy skepticism of health news while simultaneously guarding against information overload.

Related papers

• AMIR: Automated MisInformation Rebuttal -- A COVID-19 Vaccination Datasets based Recommendation System [0.05461938536945722]
  This work explored how existing information obtained from social media can be harnessed to facilitate automated rebuttal of misinformation at scale. It leverages two publicly available datasets, FaCov (fact-checked articles) and misleading (social media Twitter) data on COVID-19 Vaccination.
  arXiv  Detail & Related papers  (2023-10-29T13:07:33Z)
• Adherence to Misinformation on Social Media Through Socio-Cognitive and Group-Based Processes [79.79659145328856]
  We argue that when misinformation proliferates, this happens because the social media environment enables adherence to misinformation. We make the case that polarization and misinformation adherence are closely tied.
  arXiv  Detail & Related papers  (2022-06-30T12:34:24Z)
• "COVID-19 was a FIFA conspiracy #curropt": An Investigation into the Viral Spread of COVID-19 Misinformation [60.268682953952506]
  We estimate the extent to which misinformation has influenced the course of the COVID-19 pandemic using natural language processing models. We provide a strategy to combat social media posts that are likely to cause widespread harm.
  arXiv  Detail & Related papers  (2022-06-12T19:41:01Z)
• Cross-lingual COVID-19 Fake News Detection [54.125563009333995]
  We make the first attempt to detect COVID-19 misinformation in a low-resource language (Chinese) only using the fact-checked news in a high-resource language (English) We propose a deep learning framework named CrossFake to jointly encode the cross-lingual news body texts and capture the news content. Empirical results on our dataset demonstrate the effectiveness of CrossFake under the cross-lingual setting.
  arXiv  Detail & Related papers  (2021-10-13T04:44:02Z)
• Know it to Defeat it: Exploring Health Rumor Characteristics and Debunking Efforts on Chinese Social Media during COVID-19 Crisis [65.74516068984232]
  We conduct a comprehensive analysis of four months of rumor-related online discussion during COVID-19 on Weibo, a Chinese microblogging site. Results suggest that the dread (cause fear) type of health rumors provoked significantly more discussions and lasted longer than the wish (raise hope) type. We show the efficacy of debunking in suppressing rumor discussions, which is time-sensitive and varies across rumor types and debunkers.
  arXiv  Detail & Related papers  (2021-09-25T14:02:29Z)
• Misinformation, Believability, and Vaccine Acceptance Over 40 Countries: Takeaways From the Initial Phase of The COVID-19 Infodemic [11.737540072863405]
  This paper presents findings from a global survey on the extent of worldwide exposure to the COVID-19 infodemic. We find a strong association between perceived believability of misinformation and vaccination hesitancy. We discuss implications of our findings on public campaigns that proactively spread accurate information to countries that are more susceptible to the infodemic.
  arXiv  Detail & Related papers  (2021-04-22T05:09:25Z)
• "Thought I'd Share First" and Other Conspiracy Theory Tweets from the COVID-19 Infodemic: Exploratory Study [0.0]
  Health-related misinformation threatens adherence to public health messaging. Monitoring misinformation on social media is critical to understanding the evolution of ideas that have potentially negative public health impacts.
  arXiv  Detail & Related papers  (2020-12-14T17:24:59Z)
• Misinformation Has High Perplexity [55.47422012881148]
  We propose to leverage the perplexity to debunk false claims in an unsupervised manner. First, we extract reliable evidence from scientific and news sources according to sentence similarity to the claims. Second, we prime a language model with the extracted evidence and finally evaluate the correctness of given claims based on the perplexity scores at debunking time.
  arXiv  Detail & Related papers  (2020-06-08T15:13:44Z)
• Critical Impact of Social Networks Infodemic on Defeating Coronavirus COVID-19 Pandemic: Twitter-Based Study and Research Directions [1.6571886312953874]
  An estimated 2.95 billion people in 2019 used social media worldwide. The widespread of the Coronavirus COVID-19 resulted with a tsunami of social media. This paper presents a large-scale study based on data mined from Twitter.
  arXiv  Detail & Related papers  (2020-05-18T15:53:13Z)
• COVI White Paper [67.04578448931741]
  Contact tracing is an essential tool to change the course of the Covid-19 pandemic. We present an overview of the rationale, design, ethical considerations and privacy strategy of COVI,' a Covid-19 public peer-to-peer contact tracing and risk awareness mobile application developed in Canada.
  arXiv  Detail & Related papers  (2020-05-18T07:40:49Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.