scholarly journals THE SPREAD OF COVID-19 FAKE NEWS ON SOCIAL MEDIA AND ITS IMPACT AMONG MALAYSIANS

2021 ◽  
Vol 6 (22) ◽  
pp. 253-260
Author(s):  
Suhaila Ngadiron ◽  
Azureen Abd Aziz ◽  
Saheera Sardar Mohamed
Keyword(s):  
Economic Growth ◽  
Social Media ◽  
National Security ◽  
Detrimental Effect ◽  
Social Economic ◽  
Current Situation ◽  
Psychosocial Impact ◽  
Fake News ◽  
Common Trend

The problem of spreading fake news is not something new in this globalized era. However, nowadays, it has become a common trend among our Malaysians. In the current situation of our country Malaysia, the platform of social media is portrayed as the most suitable platform to spread rumors and fake news all over. Since the country is plagued by the Covid-19 pandemic, a variety of news and stories are served before our eyes on various social media such as WhatsApp, Facebook, Twitter, Telegram, or Instagram. These deleterious actions can actually have a detrimental effect on social, economic growth, national security as well as psychosocial impact. Findings show that information easier to obtain; easily believe in whatever they read and self-satisfaction are the main reasons for an individual who tends to have the tendency to spread fake news.

scholarly journals Social Media Infodemic During COVID-19 Outbreak

2020 ◽  
Vol 15 (4) ◽  
pp. 95-97
Author(s):  
Jeevan Bhatta ◽  
Sharmistha Sharma ◽  
Shashi Kandel ◽  
Roshan Nepal
Keyword(s):  
Public Health ◽  
Social Media ◽  
Current Situation ◽  
Fake News ◽  
Related Information ◽  
Personal Experiences ◽  
Health Related ◽  
Social Media Platforms ◽  
To Receive ◽  
Common Platform

Social media is a common platform that enables its users to share opinions, personal experiences, perspectives with one another instantaneously, globally. It has played a paramount role during pandemics such as COVID-19 and unveiled itself as a crucial means to communicate between the sources and the individuals. However, it also has become a place to disseminate misinformation and fake news rapidly. Infodemic, a plethora of information, some authentic some not makes it even harder to general people to receive factual and trustworthy information when required, has grown to be a major risk to public health and social media is developing as a trendy platform for this infodemic. This commentary aims to explore how social media has affected the current situation. We also aim to share our insight to control this misinformation.  This commentary contributes to evolving knowledge to counter fake news or health-related information shared over various social media platforms.

scholarly journals Bias Konfirmasi terhadap Perilaku Berbohong

2020 ◽  
Vol 7 (1) ◽  
pp. 21-40
Author(s):  
Fiqhiyatun Naja ◽  
Nanik Kholifah
Keyword(s):  
Social Media ◽  
Regression Analysis ◽  
National Security ◽  
Linear Regression Analysis ◽  
Confirmation Bias ◽  
Sampling Technique ◽  
Fake News ◽  
R Value ◽  
Behavior Scale ◽  
Negative Impacts

The spread of fake news in Indonesia is now increasingly widespread, especially through social media, many negative impacts have been caused from the spread of fake information. Fake information can defame the reputation of others, cruel slander, fighting between groups, and disrupt national disintegration and even disrupt national security stability. Confirmation bias is one of the reasons why someone conducts or disseminates fake information, where individuals tend to only seek and receive information that is in accordance with their thoughts and ignores different opinions that might be true facts. This study aims to measure the effect of confirmation bias on lying behavior that is prevalent around us. The sample in this study was the millennial generation of social media users who are members of the PMII Pasuruan organization of 80 members, the samples were taken by purposive sampling technique. Data collection used a lying behavior scale and a confirmation bias scale compiled by the researchers using Likert answer method. The data were then analyzed using One Predictor Linear Regression Analysis. The results of data analysis resulted r value of 0.102228 with a significance value of 0.286. This shows that there is no significant correlation between confirmation bias and lying behavior.

When Would a State Crack Down on Fake News? Explaining Variation in the Governance of Fake News in Asia-Pacific

2021 ◽  
pp. 147892992110139
Author(s):  
Ric Neo
Keyword(s):  
Economic Growth ◽  
National Security ◽  
Civil Liberties ◽  
Qualitative Comparative Analysis ◽  
Freedom Of Speech ◽  
Asia Pacific ◽  
Fake News ◽  
Media Freedom ◽  
Causal Pathways ◽  
Optimal Approach

This article sets out to explain national variation in the governance of fake news; it asks, under what conditions would governments pursue securitization in order to address the threat of fake news? Through a fuzzy-set qualitative comparative analysis of 24 countries in Asia-Pacific, this article explores multicausal explanations behind why some countries have moved to securitize fake news—framing it as an existential threat and justifying the passing of laws that curtail civil liberties—while others do not. The analysis yields two main findings. First, although prevailing political arguments emphasize the threat of fake news to society and national security as justification for the securitization of fake news, this condition is neither necessary nor sufficient in causally accounting for the decision to crackdown on fake news. Conversely, crackdowns on fake news occur more frequently in countries less affected by fake news. Second, the analysis provides a set of two distinct, theoretically and empirically relevant causal pathways explaining the decision to crack down on fake news; the first pathway shows how non-democratic states without media freedom and which are relatively less affected by fake news instrumentalize the issue to restrict freedom of speech further; the second pathway shows how non-democratic states experiencing economic growth and political turbulence with proximate elections attempt to restrict freedom of speech. The findings suggest that implementations of broad legislation may not be an optimal approach, given that they appear to be more motivated by political circumstances than by the objective resolution of the problem.

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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