Perceived Accuracy of Fake News on Social Media

Fadhila, Shnadi; Nisa, Yunita Faela; Nihayah, Zahrotun; Hayat, Bahrul; Syani, Putra Adi; Adelina, Rosa

doi:10.1109/citsm52892.2021.9588841

Cited by 3 publications

(1 citation statement)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nevertheless, the literature has produced mixed findings on the impact of gender on veracity judgments. Wolverton and Stevens (2019) and Fadhila et al (2021) report a null effect for gender, whereas Halpern et al (2019) and Pennycook and Rand (2019; although in only one of their two studies) find that female participants are worse than male participants at judging the veracity of news headlines. Note, however, that Halpern et al (2019) focus only on false news, making it challenging to distinguish between discrimination ability and response bias.…”

mentioning

confidence: 87%

Susceptibility to Online Misinformation: A Systematic Meta-Analysis of Demographic and Psychological Factors

Sultan,

Tump,

Ehmann

et al. 2024

Preprint

View full text Add to dashboard Cite

Despite a surge of research into misinformation, it is largely unclear who falls for misinformation and why. We conducted a systematic individual participant data meta-analysis covering 256,337 unique choices made by 11,561 participants across 31 experiments. Our meta-analysis reveals the impact of key demographic and psychological factors on online misinformation veracity judgments. We also disentangle the ability to discern between true and false news (discrimination ability) from the response bias, that is, a tendency to label news as either true (true-news bias) or false (false-news bias). We find that older age, higher analytic thinking skills, and identifying as a Democrat are associated with higher discrimination ability. Older age and higher analytical thinking skills are also associated with a false-news bias (caution). In contrast, ideological congruency, motivated reflection, and familiarity are associated with a true-news bias (naïvety). Our results touch upon ongoing debates in the literature and provide critical insights that can help design targeted interventions.

show abstract

mentioning

confidence: 87%

Susceptibility to Online Misinformation: A Systematic Meta-Analysis of Demographic and Psychological Factors

Sultan,

Tump,

Ehmann

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Susceptibility to online misinformation: A systematic meta-analysis of demographic and psychological factors

Sultan,

Tump,

Ehmann

et al. 2024

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Nearly five billion people use and receive news through social media and there is widespread concern about the negative consequences of misinformation on social media (e.g., election interference, vaccine hesitancy). Despite a burgeoning body of research on misinformation, it remains largely unclear who is susceptible to misinformation and why. To address this, we conducted a systematic individual participant data meta-analysis covering 256,337 unique choices made by 11,561 US-based participants across 31 experiments. Our meta-analysis reveals the impact of key demographic and psychological factors on online misinformation veracity judgments. We also disentangle the ability to discern between true and false news (discrimination ability) from response bias, that is, the tendency to label news as either true (true-news bias) or false (false-news bias). Across all studies, participants were well above-chance accurate for both true (68.51%) and false (67.24%) news headlines. We find that older age, higher analytical thinking skills, and identifying as a Democrat are associated with higher discrimination ability. Additionally, older age and higher analytical thinking skills are associated with a false-news bias (caution). In contrast, ideological congruency (alignment of participants’ ideology with news), motivated reflection (higher analytical thinking skills being associated with a greater congruency effect), and self-reported familiarity with news are associated with a true-news bias (naïvety). We also find that experiments on MTurk show higher discrimination ability than those on Lucid. Displaying sources alongside news headlines is associated with improved discrimination ability, with Republicans benefiting more from source display. Our results provide critical insights that can help inform the design of targeted interventions.

show abstract

Explainable Artificial Intelligence (XAI) on Hoax Detection Using Decision Tree C4.5 Method for Indonesian News Platform

Imanuel

Kintanswari

Thouvenot

et al. 2022

2022 International Conference of Science and Information Technology in Smart Administration (ICSINTESA)

View full text Add to dashboard Cite

Perceived Accuracy of Fake News on Social Media

Cited by 3 publications

References 36 publications

Susceptibility to Online Misinformation: A Systematic Meta-Analysis of Demographic and Psychological Factors

Susceptibility to Online Misinformation: A Systematic Meta-Analysis of Demographic and Psychological Factors

Susceptibility to online misinformation: A systematic meta-analysis of demographic and psychological factors

Explainable Artificial Intelligence (XAI) on Hoax Detection Using Decision Tree C4.5 Method for Indonesian News Platform

Contact Info

Product

Resources

About