Analyzing Biases in Perception of Truth in News Stories and Their Implications for Fact Checking

Abstract This study examines the news selection processes followed by fact-checking organizations in the Middle East, specifically Egypt, Jordan, and the United Arab Emirates, and gatekeeping such organizations face while working under authoritarian rule. By reviewing fact-checked news posted on the Facebook pages of six Arabic language organizations: Da Begad, HereszTruth, Fatabyyano, Matsad2sh, MisbarFC, and Saheeh Masr, this study manually analyzes about 5,000 fact-checked news stories to understand the extent of political fact-checking performed on Arab presidents, heads of government, and rulers, along with the most verified news topics. Results show that organizations in the Middle East rarely fact-check Arab rulers or refute their claims, while their news selection process prioritizes human interest topics. The study suggests that Arab fact-checkers resort to self-censorship due to gatekeeping influences that impact the region’s media climate.

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Intentional or inadvertent fake news sharing? Fact-checking warnings and users’ interaction with social media content

El profesional de la información ◽

10.3145/epi.2020.sep.07 ◽

2020 ◽

Cited By ~ 1

Author(s):

Alberto Ardèvol-Abreu ◽

Patricia Delponti ◽

Carmen Rodríguez-Wangüemert

Keyword(s):

Social Media ◽

Online Survey ◽

Media Content ◽

Fake News ◽

Negative Effects ◽

News Stories ◽

Social Media Platforms ◽

Fact Checking ◽

False News ◽

News Sharing

The main social media platforms have been implementing strategies to minimize fake news dissemination. These include identifying, labeling, and penalizing –via news feed ranking algorithms– fake publications. Part of the rationale behind this approach is that the negative effects of fake content arise only when social media users are deceived. Once debunked, fake posts and news stories should therefore become harmless. Unfortunately, the literature shows that the effects of misinformation are more complex and tend to persist and even backfire after correction. Furthermore, we still do not know much about how social media users evaluate content that has been fact-checked and flagged as false. More worryingly, previous findings suggest that some people may intentionally share made up news on social media, although their motivations are not fully explained. To better understand users’ interaction with social media content identified or recognized as false, we analyze qualitative and quantitative data from five focus groups and a sub-national online survey (N = 350). Findings suggest that the label of ‘false news’ plays a role –although not necessarily central– in social media users’ evaluation of the content and their decision (not) to share it. Some participants showed distrust in fact-checkers and lack of knowledge about the fact-checking process. We also found that fake news sharing is a two-dimensional phenomenon that includes intentional and unintentional behaviors. We discuss some of the reasons why some of social media users may choose to distribute fake news content intentionally.

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Asymmetric adjustment: Partisanship and correcting misinformation on Facebook

New Media & Society ◽

10.1177/14614448211021720 ◽

2021 ◽

pp. 146144482110217

Author(s):

Jay Jennings ◽

Natalie Jomini Stroud

Keyword(s):

Motivated Reasoning ◽

Asymmetric Adjustment ◽

News Stories ◽

Step Model ◽

Fact Checking ◽

Insight Into

Across two studies, we test two of Facebook’s attempts to fight misinformation: labeling misinformation as disputed or false and including fact checks as related articles. We propose hypotheses based on a two-step model of motivated reasoning, which provides insight into how misinformation is corrected. For study 1 ( n = 1,262) and study 2 ( n = 1,586), we created a mock Facebook News Feed consisting of five different articles—four were actual news stories and the fifth was misinformation. Both studies tested (a) the effect of misinformation without correction, (b) Facebook’s changes to its platform, and (c) an alternative we theorized could be more effective. The findings, in line with the two-step model of motivated reasoning, provide evidence of symmetric party effects for the belief in misinformation. In both studies, we find partisan differences in responses to fact checking. We find modest evidence that our improvements to Facebook’s attempts at correcting misinformation reduce misperceptions across partisan divides.

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Moderating with the Mob: Evaluating the Efficacy of Real-Time Crowdsourced Fact-Checking

Journal of Online Trust and Safety ◽

10.54501/jots.v1i1.15 ◽

2021 ◽

Vol 1 (1) ◽

Author(s):

William Godel ◽

Zeve Sanderson ◽

Kevin Aslett ◽

Jonathan Nagler ◽

Richard Bonneau ◽

...

Keyword(s):

Machine Learning ◽

Real Time ◽

Significant Variation ◽

Political Knowledge ◽

Third Party ◽

News Stories ◽

Social Media Platforms ◽

Fact Checking ◽

False News ◽

Wisdom Of The Crowds

Reducing the spread of false news remains a challenge for social media platforms, as the current strategy of using third-party fact- checkers lacks the capacity to address both the scale and speed of misinformation diffusion. Research on the “wisdom of the crowds” suggests one possible solution: aggregating the evaluations of ordinary users to assess the veracity of information. In this study, we investigate the effectiveness of a scalable model for real-time crowdsourced fact-checking. We select 135 popular news stories and have them evaluated by both ordinary individuals and professional fact-checkers within 72 hours of publication, producing 12,883 individual evaluations. Although we find that machine learning-based models using the crowd perform better at identifying false news than simple aggregation rules, our results suggest that neither approach is able to perform at the level of professional fact-checkers. Additionally, both methods perform best when using evaluations only from survey respondents with high political knowledge, suggesting reason for caution for crowdsourced models that rely on a representative sample of the population. Overall, our analyses reveal that while crowd-based systems provide some information on news quality, they are nonetheless limited—and have significant variation—in their ability to identify false news.

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Databases, Stories, Databases

10.1093/oso/9780190492335.003.0006 ◽

2018 ◽

Author(s):

C.W. Anderson

Keyword(s):

United States ◽

New York ◽

New York City ◽

Field Research ◽

The United States ◽

Structured Data ◽

Science Methods ◽

News Stories ◽

Social Science Methods ◽

Fact Checking

This chapter provides a history and overview of what is called “structured” journalism, journalism that grapples with a different conception of journalistic facts and the means by which these facts can be strung together to create news stories. Instead of using databases and social science methods to craft narratives, so-called computational or structured journalism turns narratives into databases; it creates structured data out of unstructured events and uses that structure to inform journalistic work and produce new news products. The chapter describes the findings of a field research project that looked at the computational journalism project Structured Stories, a structured journalism experiment in New York City, and then compares that experiment with similar projects at the BBC and to fact-checking organizations in the United States.

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Analyzing Biases in Perception of Truth in News Stories and Their Implications for Fact Checking

Proceedings of the Conference on Fairness, Accountability, and Transparency - FAT* '19 ◽

10.1145/3287560.3287581 ◽

2019 ◽

Cited By ~ 3

Author(s):

Mahmoudreza Babaei ◽

Abhijnan Chakraborty ◽

Juhi Kulshrestha ◽

Elissa M. Redmiles ◽

Meeyoung Cha ◽

...

Keyword(s):

News Stories ◽

Fact Checking

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The Effect of Searching Versus Surfing on Cognitive and Emotional Responses to Online News

Journal of Media Psychology Theories Methods and Applications ◽

10.1027/1864-1105.21.2.49 ◽

2009 ◽

Vol 21 (2) ◽

pp. 49-59 ◽

Cited By ~ 14

Author(s):

Kevin Wise ◽

Hyo Jung Kim ◽

Jeesum Kim

Keyword(s):

Heart Rate ◽

Skin Conductance ◽

Skin Conductance Level ◽

Emotional Responses ◽

Online News ◽

Self Report ◽

Mixed Design ◽

Information Need ◽

News Stories ◽

Rate Acceleration

A mixed-design experiment was conducted to explore differences between searching and surfing on cognitive and emotional responses to online news. Ninety-two participants read three unpleasant news stories from a website. Half of the participants acquired their stories by searching, meaning they had a previous information need in mind. The other half of the participants acquired their stories by surfing, with no previous information need in mind. Heart rate, skin conductance, and corrugator activation were collected as measures of resource allocation, motivational activation, and unpleasantness, respectively, while participants read each story. Self-report valence and recognition accuracy were also measured. Stories acquired by searching elicited greater heart rate acceleration, skin conductance level, and corrugator activation during reading. These stories were rated as more unpleasant, and their details were recognized more accurately than similar stories that were acquired by surfing. Implications of these results for understanding how people process online media are discussed.

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