scholarly journals Character Deprecation in Fake News: Is it in Supply or Demand?

2020 ◽  
Author(s):  
Jonathon McPhetres ◽  
David Gertler Rand ◽  
Gordon Pennycook
Keyword(s):  
Social Media ◽  
Policy Implications ◽  
Fake News ◽  
Major Focus ◽  
Analytic Thinking ◽  
Online Sources

A major focus of current research is understanding why people fall for and share fake news on social media. While much research focuses on understanding the role of personality-level traits for those who share the news, such as partisanship and analytic thinking, characteristics of the articles themselves have not been studied. Across two pre-registered studies, we examined whether character deprecation headlines—headlines designed to deprecate someone’s character, but which have no impact on policy or legislation—increased the likelihood of self-reported sharing on social media. In Study 1 we harvested fake news from online sources and compared sharing intentions between Republicans and Democrats. Results showed that, compared to Democrats, Republicans had greater intention to share character-deprecation headlines compared to news with policy implications. We then applied these findings experimentally. In Study 2 we developed a set of fake news that was matched for content across pro-Democratic and pro-Republican headlines and across news focusing on a specific person (e.g., Trump) versus a generic person (e.g., a Republican). We found that, contrary to Study 1, Republicans were no more inclined toward character deprecation than Democrats. However, these findings suggest that while character assassination may be a feature of pro-Republican news, it is not more attractive to Republicans versus Democrats. News with policy implications, whether fake or real, seems consistently more attractive to members of both parties regardless of whether it attempts to deprecate an opponent’s character. Thus, character-deprecation in fake news may in be in supply, but not in demand.

scholarly journals Character deprecation in fake news: Is it in supply or demand?

2021 ◽  
Vol 24 (4) ◽  
pp. 624-637
Author(s):  
Jonathon McPhetres ◽  
David G. Rand ◽  
Gordon Pennycook
Keyword(s):  
Social Media ◽  
Policy Implications ◽  
Fake News ◽  
Major Focus ◽  
Analytic Thinking ◽  
Online Sources

A major focus of current research is understanding why people fall for and share fake news on social media. While much research focuses on understanding the role of personality-level traits for those who share the news, such as partisanship and analytic thinking, characteristics of the articles themselves have not been studied. Across two pre-registered studies, we examined whether character-deprecation headlines – headlines designed to deprecate someone’s character, but which have no impact on policy or legislation – increased the likelihood of self-reported sharing on social media. In Study 1 we harvested fake news items from online sources and compared sharing intentions between Republicans and Democrats. Results showed that, compared to Democrats, Republicans had greater intention to share character-deprecation headlines compared to news with policy implications. We then applied these findings experimentally. In Study 2 we developed a set of fake news items that was matched for content across pro-Democratic and pro-Republican headlines and across news focusing on a specific person (e.g., Trump) versus a generic person (e.g., a Republican). We found that, contrary to Study 1, Republicans were no more inclined toward character deprecation than Democrats. However, these findings suggest that while character assassination may be a feature of pro-Republican news, it is not more attractive to Republicans versus Democrats. News with policy implications, whether fake or real, seems consistently more attractive to members of both parties regardless of whether it attempts to deprecate an opponent’s character. Thus, character deprecation in fake news may in be in supply, but not in demand.

scholarly journals Beyond “fake news”: The role of analytic thinking in the detection of inaccuracy and partisan bias in news headlines

2019 ◽  
Author(s):  
Robert M Ross ◽  
David Gertler Rand ◽  
Gordon Pennycook
Keyword(s):  
Social Media ◽  
Fake News ◽  
Analytic Thinking ◽  
Total N ◽  
Partisan Bias ◽  
News Content ◽  
Political Bias ◽  
Political Partisanship ◽  
News Headlines

Why is misleading partisan content believed and shared? An influential account posits that political partisanship pervasively biases reasoning, such that engaging in analytic thinking exacerbates motivated reasoning and, in turn, the acceptance of hyperpartisan content. Alternatively, it may be that susceptibility to hyperpartisan misinformation is explained by a lack of reasoning. Across two studies using different subject pools (total N = 1977), we had participants assess true, false, and hyperpartisan headlines taken from social media. We found no evidence that analytic thinking was associated with increased polarization for either judgments about the accuracy of the headlines or willingness to share the news content on social media. Instead, analytic thinking was broadly associated with an increased capacity to discern between true headlines and either false or hyperpartisan headlines. These results suggest that reasoning typically helps people differentiate between low and high quality news content, rather than facilitating political bias.

scholarly journals Perceived truth of statements and simulated social media postings: an experimental investigation of source credibility, repeated exposure, and presentation format

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Lena Nadarevic ◽  
Rolf Reber ◽  
Anne Josephine Helmecke ◽  
Dilara Köse
Keyword(s):  
Social Media ◽  
Source Credibility ◽  
Repeated Exposure ◽  
Presentation Format ◽  
The Internet ◽  
Additive Effects ◽  
Fake News ◽  
Source Information ◽  
Internet Age

Abstract To better understand the spread of fake news in the Internet age, it is important to uncover the variables that influence the perceived truth of information. Although previous research identified several reliable predictors of truth judgments—such as source credibility, repeated information exposure, and presentation format—little is known about their simultaneous effects. In a series of four experiments, we investigated how the abovementioned factors jointly affect the perceived truth of statements (Experiments 1 and 2) and simulated social media postings (Experiments 3 and 4). Experiment 1 explored the role of source credibility (high vs. low vs. no source information) and presentation format (with vs. without a picture). In Experiments 2 and 3, we additionally manipulated repeated exposure (yes vs. no). Finally, Experiment 4 examined the role of source credibility (high vs. low) and type of repetition (congruent vs. incongruent vs. no repetition) in further detail. In sum, we found no effect of presentation format on truth judgments, but strong, additive effects of source credibility and repetition. Truth judgments were higher for information presented by credible sources than non-credible sources and information without sources. Moreover, congruent (i.e., verbatim) repetition increased perceived truth whereas semantically incongruent repetition decreased perceived truth, irrespectively of the source. Our findings show that people do not rely on a single judgment cue when evaluating a statement’s truth but take source credibility and their meta-cognitive feelings into account.

scholarly journals Information Re-Sharing on Social Network Sites in the Age of Fake News

10.28945/3871 ◽  
2017 ◽  
Vol 20 ◽  
pp. 215-235 ◽  
Author(s):  
Mehrdad Koohikamali ◽  
Anna Sidorova
Keyword(s):  
Social Media ◽  
Social Network ◽  
Information Quality ◽  
Social Network Sites ◽  
Research Model ◽  
Fake News ◽  
Quality Of Information ◽  
Sharing Behavior

Aim/Purpose: In the light of the recent attention to the role of social media in the dissemination of fake news, it is important to understand the relationship between the characteristics of the social media content and re-sharing behavior. This study seeks to examine individual level antecedents of information re-sharing behavior including individual beliefs about the quality of information available on social network sites (SNSs), attitude towards SNS use and risk perceptions and attitudes. Methodology: Testing the research model by data collected through surveys that were adminis-tered to test the research model. Data was collected from undergraduate students in a public university in the US. Contribution: This study contributes to theory in Information Systems by addressing the issue of information quality in the context of information re-sharing on social media. This study has important practical implications for SNS users and providers alike. Ensuring that information available on SNS is of high quality is critical to maintaining a healthy user base. Findings: Results indicate that attitude toward using SNSs and intention to re-share infor-mation on SNSs is influenced by perceived information quality (enjoyment, rele-vance, and reliability). Also, risk-taking propensity and enjoyment influence the intention to re-share information on SNSs in a positive direction. Future Research: In the dynamic context of SNSs, the role played by quality of information is changing. Understanding changes in quality of information by conducting longitudinal studies and experiments and including the role of habits is necessary.

scholarly journals Detecting fake news on Facebook: The role of emotional intelligence

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0246757
Author(s):  
Stephanie Preston ◽  
Anthony Anderson ◽  
David J. Robertson ◽  
Mark P. Shephard ◽  
Narisong Huhe
Keyword(s):  
Social Media ◽  
Emotional Intelligence ◽  
Public Health Research ◽  
Fake News ◽  
Training Interventions ◽  
The Us ◽  
User Data ◽  
The Uk ◽  
Emotional Intelligence Training

The proliferation of fake news on social media is now a matter of considerable public and governmental concern. In 2016, the UK EU referendum and the US Presidential election were both marked by social media misinformation campaigns, which have subsequently reduced trust in democratic processes. More recently, during the COVID-19 pandemic, the acceptance of fake news has been shown to pose a threat to public health. Research on how to combat the false acceptance of fake news is still in its infancy. However, recent studies have started to focus on the psychological factors which might make some individuals less likely to fall for fake news. Here, we adopt that approach to assess whether individuals who show high levels of ‘emotional intelligence’ (EQ) are less likely to fall for fake news items. That is, are individuals who are better able to disregard the emotionally charged content of such items, better equipped to assess the veracity of the information. Using a sample of UK participants, an established measure of EQ and a novel fake news detection task, we report a significant positive relationship between individual differences in emotional intelligence and fake news detection ability. We also report a similar effect for higher levels of educational attainment, and we report some exploratory qualitative fake news judgement data. Our findings are discussed in terms of their applicability to practical short term (i.e. current Facebook user data) and medium term (i.e. emotional intelligence training) interventions which could enhance fake news detection.

COVID and social media

2021 ◽  
pp. 1-20
Author(s):  
Manish Puri ◽  
Zachary Dau ◽  
Aparna S. Varde
Keyword(s):  
Social Media ◽  
Public Perception ◽  
Data Science ◽  
The Public ◽  
Use Of Data ◽  
Technological Advances ◽  
The Government ◽  
Key Resources ◽  
Online Sources

The Coronavirus pandemic is one of the most devastating encounters in modern times. Over 175 million cases have been recorded globally with over 3.5 million deaths. Disseminating information to billions of people during the pandemic has been challenging, and social media has been one of the key resources for the public during these excruciating circumstances. Social media and other online sources have made it easier to access information on a variety of topics. This article presents an exploration of social media trends pertinent to information on the COVID-19 pandemic, the use of several technological advances, as well as methods for evaluating their effectiveness in combating COVID-19. We examine global case studies on the use of data from various sources to tackle COVID-19, address the issue of trust between the government and the public, and shed light on the manner in which it influences the public perception of information. We delve into the role of advances in web technology and data science in curbing COVID-19 while also touching upon the impacts in the field of smart living and healthcare. We examine studies from regions around the world, explore how the pandemic has affected people from different walks of life, and peek into the utilization of advances for disseminating information as well as curbing the spread of the virus. Additionally, we briefly discuss how the works investigated here can open pathways of research to help in further enhancing the situation as we all head towards the light at the end of the tunnel, and strive to restore global normalcy.

Evaluating the Role of News Content and Social Media Interactions for Fake News Detection

2021 ◽  
pp. 128-141
Author(s):  
Catherine Sotirakou ◽  
Anastasia Karampela ◽  
Constantinos Mourlas
Keyword(s):  
Social Media ◽  
Fake News ◽  
News Content

Fake News and Social Media Censorship

2021 ◽  
pp. 69-92
Author(s):  
Adebowale Jeremy Adetayo
Keyword(s):  
Social Media ◽  
Freedom Of Expression ◽  
Fundamental Rights ◽  
Ripple Effect ◽  
Fake News ◽  
The Public ◽  
Media Censorship

The COVID-19 pandemic has brought about a surge of fake news on social media. This dilemma has caused a ripple effect in society with increasing censorship on social media, which threatens the freedom of expression. The populace cannot effectively progress until they understand the threat posed by fake news and censorship. To protect our fundamental rights of expression, society must learn from librarians. The chapter explores the role of librarians in mitigating fake news. The chapter also identifies possible societal consequences of fake news. The chapter concludes that librarians should inoculate the public to pre-empt them from accepting fake news.

From Tracking to Trolling to Tribalism

Hard White ◽  
2020 ◽  
pp. 121-140
Author(s):  
Richard C. Fording ◽  
Sanford F. Schram
Keyword(s):  
Social Media ◽  
Mass Media ◽  
Fake News ◽  
Donald Trump ◽  
Fox News ◽  
The Mass Media

Chapter 6 focuses on the role of a changing media landscape in disseminating misinformation to a disproportionately underinformed audience to support Donald Trump. It shows how the Trump campaign and its allies, including the contract firm Cambridge Analytica as well as Russian operatives, exploited the changing media landscape to spread misinformation to sow racial division and stoke white outgroup hostility. The chapter examines the nexus between Fox News, fake news, and Trump to provide evidence of the specific connection that demonstrates the key role of the mass media, social media included, in disseminating misinformation about outgroups and sustaining high levels of outgroup hostility among whites.

Detection of conspiracy propagators using psycho-linguistic characteristics

2021 ◽  
pp. 016555152098548
Author(s):  
Anastasia Giachanou ◽  
Bilal Ghanem ◽  
Paolo Rosso
Keyword(s):  
Neural Network ◽  
Social Media ◽  
Comparative Analysis ◽  
Open Problem ◽  
Word Embeddings ◽  
Fake News ◽  
Research Attention ◽  
Conspiracy Theories ◽  
Linguistic Patterns

The rise of social media has offered a fast and easy way for the propagation of conspiracy theories and other types of disinformation. Despite the research attention that has received, fake news detection remains an open problem and users keep sharing articles that contain false statements but which they consider real. In this article, we focus on the role of users in the propagation of conspiracy theories that is a specific type of disinformation. First, we compare profile and psycho-linguistic patterns of online users that tend to propagate posts that support conspiracy theories and of those who propagate posts that refute them. To this end, we perform a comparative analysis over various profile, psychological and linguistic characteristics using social media texts of users that share posts about conspiracy theories. Then, we compare the effectiveness of those characteristics for predicting whether a user is a conspiracy propagator or not. In addition, we propose ConspiDetector, a model that is based on a convolutional neural network (CNN) and which combines word embeddings with psycho-linguistic characteristics extracted from the tweets of users to detect conspiracy propagators. The results show that ConspiDetector can improve the performance in detecting conspiracy propagators by 8.82% compared with the CNN baseline with regard to F1-metric.

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