scholarly journals Social Media and Fake News in the 2016 Election

2017 ◽  
Vol 31 (2) ◽  
pp. 211-236 ◽  
Author(s):  
Hunt Allcott ◽  
Matthew Gentzkow
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Fake News ◽  
News Stories ◽  
Social Media Networks ◽  
Data Archives ◽  
American Adult ◽  
2016 Election ◽  
False News ◽  
Election News

Following the 2016 US presidential election, many have expressed concern about the effects of false stories (“fake news”), circulated largely through social media. We discuss the economics of fake news and present new data on its consumption prior to the election. Drawing on web browsing data, archives of fact-checking websites, and results from a new online survey, we find: 1) social media was an important but not dominant source of election news, with 14 percent of Americans calling social media their “most important” source; 2) of the known false news stories that appeared in the three months before the election, those favoring Trump were shared a total of 30 million times on Facebook, while those favoring Clinton were shared 8 million times; 3) the average American adult saw on the order of one or perhaps several fake news stories in the months around the election, with just over half of those who recalled seeing them believing them; and 4) people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks.

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

2020 ◽  
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.

Spiritualism and the Resurgence of Fake News

2020 ◽  
pp. 222-237
Author(s):  
Kristy A. Hesketh
Keyword(s):  
Social Media ◽  
Mass Media ◽  
Fake News ◽  
News Stories ◽  
News Reports ◽  
The World ◽  
Spirit World ◽  
Social Media Platforms ◽  
Media Platform ◽  
False News

This chapter explores the Spiritualist movement and its rapid growth due to the formation of mass media and compares these events with the current rise of fake news in the mass media. The technology of cheaper publications created a media platform that featured stories about Spiritualist mediums and communications with the spirit world. These articles were published in newspapers next to regular news creating a blurred line between real and hoax news stories. Laws were later created to address instances of fraud that occurred in the medium industry. Today, social media platforms provide a similar vessel for the spread of fake news. Online fake news is published alongside legitimate news reports leaving readers unable to differentiate between real and fake articles. Around the world countries are actioning initiatives to address the proliferation of false news to prevent the spread of misinformation. This chapter compares the parallels between these events, how hoaxes and fake news begin and spread, and examines the measures governments are taking to curb the growth of misinformation.

scholarly journals A Reliable Artificial Intelligence Model for False News Detection Made by Public Figures

2021 ◽  
Vol 08 (03) ◽  
pp. 01-08
Author(s):  
Prashant Kumar Shrivastava ◽  
Mayank Sharma ◽  
Megha Kamble ◽  
Vaibhav Gore
Keyword(s):  
Artificial Intelligence ◽  
Social Media ◽  
Classification Accuracy ◽  
Deep Neural Networks ◽  
Access To Information ◽  
Fake News ◽  
Social Media Networks ◽  
Public Figures ◽  
False News ◽  
Research Challenge

The quick access to information on social media networks as well as its exponential rise also made it difficult to distinguish among fake information or real information. The fast dissemination by way of sharing has enhanced its falsification exponentially. It is also important for the credibility of social media networks to avoid the spread of fake information. So it is emerging research challenge to automatically check for misstatement of information through its source, content, or publisher and prevent the unauthenticated sources from spreading rumours. This paper demonstrates an artificial intelligence based approach for the identification of the false statements made by social network entities. Two variants of Deep neural networks are being applied to evalues datasets and analyse for fake news presence. The implementation setup produced maximum extent 99% classification accuracy, when dataset is tested for binary (true or false) labeling with multiple epochs.

scholarly journals Information Management in Healthcare and Environment: Towards an Automatic System for Fake News Detection

2020 ◽  
Vol 17 (3) ◽  
pp. 1066 ◽  
Author(s):  
Pablo Lara-Navarra ◽  
Hervé Falciani ◽  
Enrique A. Sánchez-Pérez ◽  
Antonia Ferrer-Sapena
Keyword(s):  
Social Media ◽  
Open Data ◽  
The Internet ◽  
Web Pages ◽  
Fake News ◽  
Social Media Networks ◽  
Analytical Scheme ◽  
False News ◽  
The Right ◽  
Methodological Guidelines

Comments and information appearing on the internet and on different social media sway opinion concerning potential remedies for diagnosing and curing diseases. In many cases, this has an impact on citizens’ health and affects medical professionals, who find themselves having to defend their diagnoses as well as the treatments they propose against ill-informed patients. The propagation of these opinions follows the same pattern as the dissemination of fake news about other important topics, such as the environment, via social media networks, which we use as a testing ground for checking our procedure. In this article, we present an algorithm to analyse the behaviour of users of Twitter, the most important social network with respect to this issue, as well as a dynamic knowledge graph construction method based on information gathered from Twitter and other open data sources such as web pages. To show our methodology, we present a concrete example of how the associated graph structure of the tweets related to World Environment Day 2019 is used to develop a heuristic analysis of the validity of the information. The proposed analytical scheme is based on the interaction between the computer tool—a database implemented with Neo4j—and the analyst, who must ask the right questions to the tool, allowing to follow the line of any doubtful data. We also show how this method can be used. We also present some methodological guidelines on how our system could allow, in the future, an automation of the procedures for the construction of an autonomous algorithm for the detection of false news on the internet related to health.

Survey on Fake News or Truth - Rumours Detection using Machine Learning

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Kalyani Deore ◽  
Leena Gaikwad ◽  
Rohit Dhamne ◽  
Vishal Agale ◽  
T. Bhaskar
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Machine Learning Algorithms ◽  
Modern World ◽  
Fake News ◽  
Misleading Information ◽  
Original Source ◽  
News Stories ◽  
False News ◽  
Communication Methods

This study is to help readers to understand detection of fake news using machine learning. The main purpose of the planned system is to build an application which identifies fake news stories from a bunch of news stories to make people aware of fake news rumours. With the help of machine learning algorithms, we can detect and separate out the fake news. Nowadays, it is become harder to identify the original source of news stories, like looking for a needle in a haystack. In the modern world, news is a kind of communication that keeps us up to date on the latest events, topics, and people in the wider globe. A society relies on news for a variety of reasons, the most important of which is informing its members about events taking on in and around them that might influence them. Oral and traditional media, as well as digital communication methods, altered videos, memes, unconfirmed marketing, and social media have all contributed to the spread of rumors. As nowadays many people use social media in many cases people get wrong and misleading information and people share those stories without verifying whether it is real or fake news stories. Spreading false information on social media has become a major problem these days. That is why we need a system that can tell us whether something is false news or not. Applications are: 1. Fake news may be detected on social media using this approach. 2. The system can be used to help news channels to broadcast only real and classified news. 3. Users can easily detect and eliminate fake articles that contain misinformation intended to mislead readers.

Fake News

2018 ◽  
Author(s):  
Leticia Bode ◽  
Emily K. Vraga ◽  
Kjerstin Thorson
Keyword(s):  
Social Media ◽  
Presidential Elections ◽  
Fake News ◽  
News Stories ◽  
The World ◽  
Different Types ◽  
2016 Election ◽  
Use Of Social Media ◽  
Insight Into

Chapter 7 tackles the challenges posed by misinformation campaigns and fake news, an issue of growing concern in America and around the world. Following the 2016 U.S. presidential elections, academics and pundits alike struggled to make sense of what happened, and many pointed to the role of fake news and misinformation more broadly in leading voters astray in their assessments of the two major candidates for president. This chapter draws on survey data to investigate how media use in general, and use of social media and partisan media more specifically, affected belief in six fake news stories directly following the 2016 election. The analysis assesses whether use of different types of media affected belief in misinformation—including messages congruent and incongruent with their own candidate preferences—providing insight into what was to blame for belief in fake news in the 2016 elections.

Social media, fake news and fake COVID-19 cures in Nigeria

2021 ◽  
Vol 13 (3) ◽  
pp. 435-449 ◽  
Author(s):  
Temple Uwalaka ◽  
Bigman Nwala ◽  
Amadi Confidence Chinedu
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Fake News ◽  
News Stories ◽  
News Consumption ◽  
Using Data ◽  
The Impact ◽  
News Headlines

This study investigates the impact of social media ‘fake news’ and fake cures headlines on how Netizens viewed and responded to the COVID-19 pandemic in Nigeria. Using data from an online survey (N=254), this study reveals that social media was overwhelmingly the most used type of media for news consumption generally, and the most important source of news about the pandemic. Data further reveal that the impact of extensive exposure to fake news headlines about the pandemic was dangerous and could have a deleterious impact. Crucially, this study finds that recalling and believing fake news headlines and using social media as the main source of news, significantly decreases the likelihood of believing credible and real news stories. Finally, this study offers theoretical and empirical background to frame the debate about factors that influence the believability of fake news headlines by contributing and extending the theorization of the amplification hypothesis.

scholarly journals ‘INFORMATION DISORDER’: SAMPLE OF SYRIANS IN TURKEY

2021 ◽  
pp. 109-122
Author(s):  
Apak Kerem ALTINTOP ◽  
Yasin ÖZBEY ◽  
Ece ÇİM
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Age Distribution ◽  
Active Role ◽  
University Graduates ◽  
Fake News ◽  
Temporary Protection ◽  
The Media ◽  
Concept Of Information ◽  
False News

The aim of the study is to examine perceptions and knowledge towards Syrians in Turkey under temporary protection. This examination will be conducted in the light of the concept of information disorder that was conceptualized by Wardle in 2017. The concepts of "fake news", "false content", "disinformation" in the current literature assume that the information is wrong. Information disorder is based on two bases: i) whether the information is true or false, ii) what is the intention of producing, sharing, and disseminating information. In the research, the news about Syrians in the media and that set an example for information disorder was examined. Then, the knowledge and perception of the society was investigated through the relevant news. Qualitative method was preferred in the study. An online survey was conducted because of the COVID-19 outbreak. 360 people were reached. The survey consists of questions about false news about Syrians in the media, social media usage habits, sharing habits and demographic information. While 60.4% of the participants in the study are women, 38.5% are men. The age distribution is between the ages of 17-70. The average age is 35.55. Most of the participants are university graduates (57.1%). The rate of those who had family or personal immigration experience before is 44.9%. While 74.2% of the participants do not share the news about Syrians on social media, most of those who share are made on Twitter. As a result, social media plays an active role in the circulation of fake news, which occupies a certain place in the country, without confirmation and origin, and creates social reality. Although people think that they use it consciously, it is seen that they think differently when it comes to Syrian under temporary protection.

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.

scholarly journals Advancing children’s news media literacy: learning from the practices and experiences of young Australians

2018 ◽  
Vol 41 (5) ◽  
pp. 689-707
Author(s):  
Tanya Notley ◽  
Michael Dezuanni
Keyword(s):  
Social Media ◽  
Media Literacy ◽  
News Media ◽  
Social Impact ◽  
Literacy Learning ◽  
Literacy Education ◽  
Fake News ◽  
News Stories ◽  
Media Literacy Education ◽  
Nationally Representative

Social media use has redefined the production, experience and consumption of news media. These changes have made verifying and trusting news content more complicated and this has led to a number of recent flashpoints for claims and counter-claims of ‘fake news’ at critical moments during elections, natural disasters and acts of terrorism. Concerns regarding the actual and potential social impact of fake news led us to carry out the first nationally representative survey of young Australians’ news practices and experiences. Our analysis finds that while social media is one of young people’s preferred sources of news, they are not confident about spotting fake news online and many rarely or never check the source of news stories. Our findings raise important questions regarding the need for news media literacy education – both in schools and in the home. Therefore, we consider the historical development of news media literacy education and critique the relevance of dominant frameworks and pedagogies currently in use. We find that news media has become neglected in media literacy education in Australia over the past three decades, and we propose that current media literacy frameworks and pedagogies in use need to be rethought for the digital age.

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