Combating Fake News on Social Media with Source Ratings: The Effects of User and Expert Reputation Ratings

Kim, Antino; Moravec, Patricia L.; Dennis, Alan R.

doi:10.1080/07421222.2019.1628921

Cited by 199 publications

(201 citation statements)

References 46 publications

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“…Studies examining whether differences in news organization credibility can affect perceptions of news veracity have been similarly inconclusive. Many studies have found that source credibility can affect judgments of accuracy or believability (Baum & Groeling, 2009;Landrum et al, 2017;Berinsky, 2017;Swire et al, 2017;Knight Foundation, 2018;Kim et al, 2019). Yet, others (Austin & Dong, 1994, Pennycook & Rand, 2019b, Jakesch et al, 2018 have failed to demonstrate that assessments of news stories are changed by source information.…”

Section: Implications (Why Does This Matter? and To Whom?)mentioning

confidence: 99%

Emphasizing publishers does not effectively reduce susceptibility to misinformation on social media

Dias¹,

Pennycook²,

Rand³

2020

Preprint

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Section: Implications (Why Does This Matter? and To Whom?)mentioning

confidence: 99%

Emphasizing publishers does not effectively reduce susceptibility to misinformation on social media

Dias¹,

Pennycook²,

Rand³

2020

Preprint

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“…One possible explanation given by the authors is that people generally do not read health information for entertainment but rather search for information useful to their health or that of people close to them. Furthermore, in these cases, they are less likely to have a pre-existing opinion about health information than are those who share fake news stories about other topics [34]. A similar conclusion came from a fact-checking study of Twitter and Sina Weibo (the most-used social media platform in China), developed 24 hours after the WHO's declaration of the Ebola outbreak as a Public Health Emergency of International Concern in August 2014.…”

Section: Fake News Health and Social Mediamentioning

confidence: 87%

“…However, data cannot support the contention that novelty is the only reason, or the main reason, for the spreading of falsehood [13,32]. However, other studies that have focused on the analysis of fake news in social media have reached different conclusions [33,34].…”

Section: Fake News Health and Social Mediamentioning

confidence: 90%

“…These techniques include both human intervention and algorithms to verify the veracity of information across technologies, such as artificial intelligence (AI) and natural language processing (NLP) [44]. Other mechanisms developed as a remedy against fake news on social media are source ratings that can be applied to articles when they are initially published, such as expert ratings (in which expert reviewers fact check articles-the results of which are aggregated to provide a source rating), user article ratings (in which users rate articles-the results of which are aggregated to provide a source rating), and user source ratings (in which users rate the sources themselves) [34].…”

Section: Combating Fake News On Social Mediamentioning

confidence: 99%

See 1 more Smart Citation

A New Application of Social Impact in Social Media for Overcoming Fake News in Health

Pulido

Ruiz-Eugenio

Redondo-Sama

et al. 2020

IJERPH

153

111

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One of the challenges today is to face fake news (false information) in health due to its potential impact on people's lives. This article contributes to a new application of social impact in social media (SISM) methodology. This study focuses on the social impact of the research to identify what type of health information is false and what type of information is evidence of the social impact shared in social media. The analysis of social media includes Reddit, Facebook, and Twitter. This analysis contributes to identifying how interactions in these forms of social media depend on the type of information shared. The results indicate that messages focused on fake health information are mostly aggressive, those based on evidence of social impact are respectful and transformative, and finally, deliberation contexts promoted in social media overcome false information about health. These results contribute to advancing knowledge in overcoming fake health-related news shared in social media.

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“…The coverage of social media tends to meet public preference and seek sensational effects [63]. There exist widespread biases and exaggerations in social media reports [64,65]. In the long run, relying heavily on social media in regulation may bring some serious consequences, such as the unscrupulous social media may pose a potentially unfair threat to the companies [66].…”

Section: Futher Discussion About State 3 and Statementioning

confidence: 99%

Dynamic Evolution of Safety Regulation of the Ridesharing Industry under Social Media Participation

Sun

et al. 2020

Symmetry

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The emergence of ridesharing has spread against the background of the sharing economy. There have been a lot of controversies since the emergence of ridesharing, particularly regarding regulatory issues. The safety regulation of the ridesharing industry involves many parties, including governments, platform companies, and society at large. Currently, because of the influence of information asymmetry, it increases the uncertainty of governments’ regulation effect and the difficulty of making regulation measures. Meanwhile, social media, one of the most important forces of social regulation, has not paid enough attention to playing an appropriate role in the safety regulation of the ridesharing industry. Therefore, this study constructs an evolutionary game model between governments and platform companies that concerns the safety regulations of ridesharing passengers under social media participation. The influence path of social media is explored by model solution and numerical simulation. Our results indicate that social media participation has a positive impact on this safety regulation. Specifically, social media participation could reduce governments’ regulatory costs and encourage it to strictly regulate. The exposure of social media could bring losses to platform companies involved and promote platform companies’ investments in improving passengers’ safety. This study provides a decision basis for governments to introduce social media in the safety regulation of the ridesharing industry.

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Combating Fake News on Social Media with Source Ratings: The Effects of User and Expert Reputation Ratings

Cited by 199 publications

References 46 publications

Emphasizing publishers does not effectively reduce susceptibility to misinformation on social media

Emphasizing publishers does not effectively reduce susceptibility to misinformation on social media

A New Application of Social Impact in Social Media for Overcoming Fake News in Health

Dynamic Evolution of Safety Regulation of the Ridesharing Industry under Social Media Participation

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