In Related News, That Was Wrong: The Correction of Misinformation Through Related Stories Functionality in Social Media

By Leticia Bode, Emily K. Vraga. 2015

558 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Communication, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/bddbaf4a45dd35c386a9bdea16b3ef2d90b2967e

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Citations in the corpus

Systematic Literature Review on the Spread of Health-related Misinformation on Social Media (2019, background): “Bode and Vraga, in three different papers, manipulated Facebook's "related news" function to confirm or correct (or both) misinformation about the purported link between vaccines and autism, as well as unfounded link between genetically modified organisms (GMO) and health (Bode and Vraga, 2015; Vrag”
Educative Interventions to Combat Misinformation: Evidence from a Field Experiment in India (2020, background): “These include providing warning labels on articles, attaching disputed tags to misinformation, and providing corrective information beside fake claims (Bode and Vraga 2015; Pennycook, Cannon, and Rand 2018; Clayton et al. 2019; Nyhan et al. 2019).”
Creating News Literacy Messages to Enhance Expert Corrections of Misinformation on Twitter (2020, background): “They may engage in confirmation bias (Taber & Lodge, 2006) and evaluate the correction poorly as a result (Bode & Vraga, 2015), but viewing the correction still decreases misperceptions.”
Testing the Effectiveness of Correction Placement and Type on Instagram (2020, methodology): “One study found correction message credibility mediated misperceptions regarding the Zika virus, but the specific pathways differed on Facebook versus Twitter (Vraga and Bode 2018).”
Credibility Perceptions and Detection Accuracy of Fake News Headlines on Social Media: Effects of Truth-Bias and Endorsement Cues (2020, background): “From the perspective of information processing, a burgeoning literature has examined how individuals process fake news, such as how motivated reasoning can drive false beliefs about controversial political and health issues (e.g., the existence of Weapons of Mass Destruction in Iraq, Nyhan & Reifler”
Evaluating the Impact of Attempts to Correct Health Misinformation on Social Media: A Meta-Analysis (2020, background): “When the source of misinformation was a news agency (e.g., Washington Post) but the message was shared by a private social media user (e.g., random person’s Newsfeed), the misinformation was attributed to the news agency (e.g., Bode & Vraga, 2015).”
Testing Logic-based and Humor-based Corrections for Science, Health, and Political Misinformation on Social Media (2019, background): “…research into observational correction has found effects tend be stronger among those who have higher pre-existing misperceptions on the issue (Bode & Vraga, 2015; Vraga & Bode, 2017), but other research has found that corrections largely reduce misperceptions among those who already hold…”
The Debunking Handbook 2020 (2020, unknown): “Individuals have the ability to make a difference online: Corrections from users, experts, and algorithms (e.g., recommending related articles that contain a correction) can all be effective in reducing community misperceptions when responding to misinformation 103, 104, 105 .”
Public Health and Online Misinformation: Challenges and Recommendations. (2019, background): “Misinformation and disinformation are introduced online by many different sources: vested interests, politicians (120), news media (12), gossip, and works of fiction (71).”
Correction Experiences on Social Media During COVID-19 (2021, background): “This includes seeing a fact-check (Ecker et al., 2020), a correction from a platform (Bode & Vraga, 2015), or another social media user refuting a claim (Margolin et al., 2018).”
All the News That’s Fit to Click: The Economics of Clickbait Media (2019, background): “…settings, studies have shown various degrees of success in correcting misinformation, with partisans being less likely to accept that an ideologically congruent belief is false (Bode & Vraga, 2015; Garrett, Nisbet, & Lynch, 2013; Nyhan & Reifler, 2010; Nyhan, Reifler, Richey, & Freed, 2014).”
See Something, Say Something: Correction of Global Health Misinformation on Social Media (2018, background): “Our previous research (Bode & Vraga, 2015) found that even though individuals who (falsely) believe genetically modified organisms (GMOs) cause illness reported lower credibility ratings for stories that debunk that misinformation, they still showed a significant decline in their misperceptions on…”
“Fake News” Is Not Simply False Information: A Concept Explication and Taxonomy of Online Content (2019, background): “This is particularly troublesome given that individuals find information that agrees with prior beliefs as more credible and reliable, creating an environment that exacerbates misinformation because credible information appears alongside personal opinions (Bode & Vraga, 2015).”
Filter Bubbles, Echo Chambers, and Fake News: How Social Media Conditions Individuals to Be Less Critical of Political Misinformation (2021, background): “The second of these two forces dictating exposure to fake news is not solely based on “the friends we select or what those friends post” (Bode & Vraga, 2015, p. 620), but on the algorithmically powered filter bubbles working behind-the-scenes.”
Effects of COVID-19 Misinformation on Information Seeking, Avoidance, and Processing: A Multicountry Comparative Study (2020, background): “Such selective information exposure and motivated reasoning make it difficult to rectify misinformation once false beliefs are deeply held (Bode & Vraga, 2015; Jerit & Barabas, 2012).”
Misinformation on Instagram: The Impact of Trusted Endorsements on Message Credibility (2020, background): “Future research also may explore message credibility across different platforms to understand how Instagram differs from Facebook and Twitter regarding credibility when the same message and stimuli are used.”
Fake news, disinformation and misinformation in social media: a review (2023, background): “…news (Vraga and Bode 2017; Jakesch et al. 2019; Shen et al. 2019; Avram et al. 2020; Hameleers et al. 2020; Dias et al. 2020; Nyhan et al. 2020; Bode and Vraga 2015; Tsang 2020; Vishwakarma et al. 2019; Yavary et al. 2020) and investigate fake and reliable news sources using complex networks…”