scholarly journals A Perfect Storm

2021 ◽  
Vol 2 (2) ◽  
pp. 1-21
Author(s):  
Pratim Datta ◽  
Mark Whitmore ◽  
Joseph K. Nwankpa
Keyword(s):  
Social Media ◽  
Theoretical Framework ◽  
Integrative Model ◽  
Fake News ◽  
Policy Makers ◽  
Human Psychology ◽  
Technology Firms ◽  
Information Bias ◽  
Explainable Ai ◽  
Perfect Storm

In an age where news information is created by millions and consumed by billions over social media ( SM ) every day, issues of information biases, fake news, and echo-chambers have dominated the corridors of technology firms, news corporations, policy makers, and society. While multiple disciplines have tried to tackle the issue using their disciplinary lenses, there has, hitherto, been no integrative model that surface the intricate, albeit “dark” explainable AI confluence of both technology and psychology. Investigating information bias anchoring as the overarching phenomenon, this research proposes a theoretical framework that brings together traditionally fragmented domains of AI technology, and human psychology. The proposed Information Bias Anchoring Model reveals how SM news information creates an information deluge leading to uncertainty, and how technological rationality and individual biases intersect to mitigate the uncertainty, often leading to news information biases. The research ends with a discussion of contributions and offering to reduce information bias anchoring.

Political psychology in the digital (mis)information age: A model of news belief and sharing

2020 ◽  
Author(s):  
Jay Joseph Van Bavel ◽  
Elizabeth Ann Harris ◽  
Philip Pärnamets ◽  
Steve Rathje ◽  
Kimberly Doell ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cognitive Psychology ◽  
Information Age ◽  
Policy Research ◽  
Integrative Model ◽  
Future Research ◽  
Fake News ◽  
Policy Makers ◽  
Conspiracy Theories ◽  
The Social

The spread of misinformation, including “fake news,” propaganda, and conspiracy theories, represents a serious threat to society, as it has the potential to alter beliefs, behavior, and policy. Research is beginning to disentangle how and why misinformation is spread and identify processes that contribute to this social problem. We propose an integrative model to understand the social, political, and cognitive psychology risk factors that underlie the spread of misinformation and highlight strategies that might be effective in mitigating this problem. However, the spread of misinformation is a rapidly growing and evolving problem; thus scholars need to identify and test novel solutions, and work with policy makers to evaluate and deploy these solutions. Hence, we provide a roadmap for future research to identify where scholars should invest their energy in order to have the greatest overall impact.

‘Fake news’ – the perfect storm: historical perspectives*

2020 ◽  
Vol 93 (259) ◽  
pp. 172-187 ◽  
Author(s):  
Jo Fox
Keyword(s):  
Social Media ◽  
Liberal Democracy ◽  
Political System ◽  
The Internet ◽  
Fake News ◽  
Recent Past ◽  
Historical Perspectives ◽  
Psychological Warfare ◽  
Wild West ◽  
Perfect Storm

Abstract What is ‘fake news’? Undoubtedly, the phenomenon has become one of the defining characteristics of our recent past – in 2016 Oxford Dictionaries defined ‘post-truth’ to be its ‘word of the year’. But what might its significance be 100 years from now, and how ‘new’ is ‘fake news’? This article reflects on propaganda in the twentieth and twenty-first centuries to argue that we now face the ‘perfect storm’: the speed, scope and scale of modern communications, complicated by the uncertain status of social media as neither platform nor publisher and the hidden algorithms used to control the information we see; the building frustration of those who feel disempowered by elites; the desire of some to destabilize the entire social and political system through psychological warfare campaigns and by creating a situation where all views are of equal value regardless of the evidential base; where psychological warriors can operate under the radar in the largely unregulated ‘wild west’ of the internet. But what is genuinely new about this situation, and how might history help us to find appropriate solutions to ‘fake news’ within a liberal democracy?

Says Who? The Effects of Presentation Format and Source Rating on Fake News in Social Media

MIS Quarterly ◽  
2019 ◽  
Vol 43 (3) ◽  
pp. 1025-1039 ◽  
Author(s):  
Antino Kim ◽  
◽  
Alan R. Dennis ◽  
Keyword(s):  
Social Media ◽  
Presentation Format ◽  
Fake News

Identity concerns drive belief: The impact of partisan identity on the belief and dissemination of true and false news

2018 ◽  
Author(s):  
Andrea Pereira ◽  
Jay Joseph Van Bavel ◽  
Elizabeth Ann Harris
Keyword(s):  
Social Media ◽  
Political System ◽  
Political Identity ◽  
Social Goals ◽  
Fake News ◽  
Political Beliefs ◽  
System P ◽  
False News ◽  
Democrats And Republicans ◽  
The Impact

Political misinformation, often called “fake news”, represents a threat to our democracies because it impedes citizens from being appropriately informed. Evidence suggests that fake news spreads more rapidly than real news—especially when it contains political content. The present article tests three competing theoretical accounts that have been proposed to explain the rise and spread of political (fake) news: (1) the ideology hypothesis— people prefer news that bolsters their values and worldviews; (2) the confirmation bias hypothesis—people prefer news that fits their pre-existing stereotypical knowledge; and (3) the political identity hypothesis—people prefer news that allows their political in-group to fulfill certain social goals. We conducted three experiments in which American participants read news that concerned behaviors perpetrated by their political in-group or out-group and measured the extent to which they believed the news (Exp. 1, Exp. 2, Exp. 3), and were willing to share the news on social media (Exp. 2 and 3). Results revealed that Democrats and Republicans were both more likely to believe news about the value-upholding behavior of their in-group or the value-undermining behavior of their out-group, supporting a political identity hypothesis. However, although belief was positively correlated with willingness to share on social media in all conditions, we also found that Republicans were more likely to believe and want to share apolitical fake new. We discuss the implications for theoretical explanations of political beliefs and application of these concepts in in polarized political system.

Fake It “Till You Make It”: Debunking Fake News in a Post-Truth America

2019 ◽  
Vol 8 (1) ◽  
pp. 114-133
Keyword(s):  
Social Media ◽  
First Amendment ◽  
Presidential Election ◽  
Political Discourse ◽  
Cutting Edge ◽  
American People ◽  
Fake News ◽  
News Sources ◽  
The Media ◽  
The U.S

Since the 2016 U.S. presidential election, attacks on the media have been relentless. “Fake news” has become a household term, and repeated attempts to break the trust between reporters and the American people have threatened the validity of the First Amendment to the U.S. Constitution. In this article, the authors trace the development of fake news and its impact on contemporary political discourse. They also outline cutting-edge pedagogies designed to assist students in critically evaluating the veracity of various news sources and social media sites.

scholarly journals Credibility of Digital Political News in Spain: Comparison between Traditional Media and Social Media

2021 ◽  
Vol 10 (5) ◽  
pp. 170
Author(s):  
Reinald Besalú ◽  
Carles Pont-Sorribes
Keyword(s):  
Social Media ◽  
News Item ◽  
Digital Television ◽  
Fake News ◽  
Traditional Media ◽  
Political News ◽  
Digital News ◽  
Key Factor ◽  
The Mean ◽  
Digital Formats

In the context of the dissemination of fake news and the traditional media outlets’ loss of centrality, the credibility of digital news emerges as a key factor for today’s democracies. The main goal of this paper was to identify the levels of credibility that Spanish citizens assign to political news in the online environment. A national survey (n = 1669) was designed to assess how the news format affected credibility and likelihood of sharing. Four different news formats were assessed, two of them linked to traditional media (digital newspapers and digital television) and two to social media (Facebook and WhatsApp). Four experimental groups assigned a credibility score and a likelihood of sharing score to four different political news items presented in the aforementioned digital formats. The comparison between the mean credibility scores assigned to the same news item presented in different formats showed significant differences among groups, as did the likelihood of sharing the news. News items shown in a traditional media format, especially digital television, were assigned more credibility than news presented in a social media format, and participants were also more likely to share the former, revealing a more cautious attitude towards social media as a source of news.

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.

Exploring fake news identification using word and sentence embeddings

2021 ◽  
pp. 1-8
Author(s):  
V.T Priyanga ◽  
J.P Sanjanasri ◽  
Vijay Krishna Menon ◽  
E.A Gopalakrishnan ◽  
K.P Soman
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Network Analysis ◽  
Supervised Machine Learning ◽  
Breeding Ground ◽  
Fake News ◽  
Data Set ◽  
Highly Correlated ◽  
Use Of Social Media ◽  
The Liar

The widespread use of social media like Facebook, Twitter, Whatsapp, etc. has changed the way News is created and published; accessing news has become easy and inexpensive. However, the scale of usage and inability to moderate the content has made social media, a breeding ground for the circulation of fake news. Fake news is deliberately created either to increase the readership or disrupt the order in the society for political and commercial benefits. It is of paramount importance to identify and filter out fake news especially in democratic societies. Most existing methods for detecting fake news involve traditional supervised machine learning which has been quite ineffective. In this paper, we are analyzing word embedding features that can tell apart fake news from true news. We use the LIAR and ISOT data set. We churn out highly correlated news data from the entire data set by using cosine similarity and other such metrices, in order to distinguish their domains based on central topics. We then employ auto-encoders to detect and differentiate between true and fake news while also exploring their separability through network analysis.

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