scholarly journals "Die-Hard Supporters"

2021 ◽  
Vol 14 (2) ◽  
pp. 86-118
Author(s):  
Danna Aranda
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Thematic Analysis ◽  
Group Behavior ◽  
Media Campaign ◽  
Fake News ◽  
Networked System ◽  
Online Platforms ◽  
2016 Election ◽  
Group Members

The success of the maverick politician Rodrigo Duterte in the 2016 election is cited as a result of the weaponization of social media—whereby professional, tech-savvy strategists mobilized public opinion through a networked system of disinformation. Yet, there is evidence of grassroots campaign support that emerged via online platforms. Those who have mobilized include Overseas Filipino Workers (OFWs), who have used Facebook groups to rally in support of Duterte. This research looks at the activities of two OFW Facebook groups to understand precisely how and why they organized for Duterte. Employing a dualstage thematic analysis on posts and comments by group members between March 28 – May 9, 2016, three key findings emerged. First, motivations for supporting Duterte varied greatly among users and are far more complex than Duterte’s mandate to crack-down on corruption, crime, and drugs. Second, group behavior deviates from top-heavy explanations of online campaign mobilization, as these groups operated autonomously from Duterte’s official campaign. Finally, these groups were not amorphous and had, as the most active members and organizers, certain intermediaries. These grassroots intermediaries sought to amplify support for Duterte by organizing events, using diversionary tactics, and helping to propagate fake news. These findings suggest that while these groups were operating independently, they were not devoid of influence from Duterte’s official social media campaign.

OPINI PUBLIK TERHADAP PENERAPAN NEW NORMAL DI MEDIA SOSIAL TWITTER

2020 ◽  
Vol 11 (1) ◽  
pp. 19-26
Author(s):  
AWAD BIN MUHAMMAD ALKATIRI ◽  
ZHAFIRA NADIAH ◽  
ADINDA NADA S. NASUTION
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Public Opinion ◽  
Thematic Analysis ◽  
Research Method ◽  
Age Groups ◽  
Validity And Reliability ◽  
New Normal ◽  
Quantitative Content ◽  
The Social

Social media is popular with all ages, people in young and old age groups can access social media. Social media is a place for information and opinion exchange. Twitter is one of the social media that is actively used in Indonesia. The new normal phenomenon that is currently being applied is wanted to be further known by researchers by referring to the hashtag #newnormalindonesia on Twitter. Researchers want to find out how public opinion is formed based on the hashtag #newnormalindonesia on Twitter. This research uses the concept of public opinion which is categorized into positive, negative, and neutral. In the research method, researchers use quantitative content analysis, the analysis unit uses thematic analysis units with the operationalization of concepts using the concept of public opinion. Coding sheets are used as instruments in data collection techniques, then in testing the validity and reliability using inter-coder reliability. The results showed that the twitter posts with the #newnormalindonesia hashtag tendto be negative by not supporting the implementation of new normal.

Statistical Methods for Conducting the Ontology and Classifications of Fake News on Social Media

2021 ◽  
pp. 632-651
Author(s):  
Joshua Ojo Nehinbe
Keyword(s):  
Social Media ◽  
Thematic Analysis ◽  
Cyber Security ◽  
Social Dynamics ◽  
Research Community ◽  
Contemporary Society ◽  
Fake News ◽  
Religious Issues ◽  
Classical Studies ◽  
Political Rivalry

Fake news and its impacts are serious threats to social media in recent time. Studies on the ontology of these problems reveal that serious cybercrimes such as character assassination, misinformation, and blackmailing that some people intentionally perpetrate through social networks significantly correlate with fake news. Consequently, some classical studies on social anthropology have profiled the problems and motives of perpetrators of fake news on political, rivalry, and religious issues in contemporary society. However, this classification is restrictive and statistically defective in dealing with cyber security, forensic problems, and investigation of social dynamics on social media. This chapter exhaustively discusses the above issues and identifies solutions to challenges confronting research community in the above domain. Thematic analysis of responses of certain respondents reveal three new classifications of fake news that people propagate on social media on the basis of mode of propagation, motives of perpetrators, and impacts on victims.

Tweeting Grenfell: Discourse and networks in critical constructions of British Muslim social boundaries on social media

2019 ◽  
Vol 22 (3) ◽  
pp. 449-469 ◽  
Author(s):  
Joseph Downing ◽  
Richard Dron
Keyword(s):  
Social Media ◽  
Social Network ◽  
Thematic Analysis ◽  
Hate Speech ◽  
Social Boundaries ◽  
Fake News ◽  
International Space ◽  
British Muslims ◽  
Per Se ◽  
Methodological Approaches

The Grenfell fire has yet to be analysed to understand the event’s implications in relation to construction of social boundaries for British Muslims. In this current research, two methodological approaches are applied to gain understandings of social boundary construction on twitter: thematic analysis of the content of tweets and social network analysis (SNA) of how messages are diffused and contested. Twitter is shown to be an important platform in spreading positive narratives about Muslims during the fire, enabling individuals to spontaneously contest fake news and hate narratives. Social media acts counter to established knowledge, demonstrating that it is not, per se, a conduit for fake news and hate speech. Furthermore, it demonstrates how twitter offers Muslims an international space to voice and articulate themselves where they can be influential in debates that effect Muslim diasporas in other national contexts.

scholarly journals Detecting Fake News using Machine Learning: A Systematic Literature Review

2021 ◽  
Vol 58 (1) ◽  
pp. 1932-1939
Author(s):  
Alim Al Ayub Ahmed Et al.
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Political Party ◽  
Fake News ◽  
Machine Learning Classifiers ◽  
Online Platforms ◽  
Learning Classifiers ◽  
Social Media Platforms

Internet is one of the important inventions and a large number of persons are its users. These persons use this for different purposes. There are different social media platforms that are accessible to these users. Any user can make a post or spread the news through these online platforms. These platforms do not verify the users or their posts. So some of the users try to spread fake news through these platforms. These fake news can be a propaganda against an individual, society, organization or political party. A human being is unable to detect all these fake news. So there is a need for machine learning classifiers that can detect these fake news automatically. Use of machine learning classifiers for detecting the fake news is described in this systematic literature review.

Bad News

2021 ◽  
pp. 240-260
Author(s):  
Debasish Roy Chowdhury ◽  
John Keane
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Communication Networks ◽  
Bad News ◽  
Fake News ◽  
Media Environment ◽  
Media Frames ◽  
Mainstream Media ◽  
Bharatiya Janata Party ◽  
Media Communications

This chapter examines Indian media. Communications scholars have long argued that media sets the agenda for public opinion, first by drawing the attention of citizens to a particular issue, and then by defining it by means of comprehensible media ‘frames’ that act as cognitive shortcuts to understand issues. As in other so-called democracies, journalists working within India’s mainstream media are engaged 24/7 in framing narratives, making them indispensable for any government. Anti-Muslim messaging, generally subtle, has been the default media frame ever since the Hindu nationalist Bharatiya Janata Party (BJP) came to power in 2014. This coincided with the coming of communicative abundance, the profusion of new communication networks and technologies, and rapidly changing media consumption habits. Secretive organizations frame sophisticated misinformation campaigns to spread fake news and false claims through social media. In such a media environment marked by features common to despotisms like Vietnam, Iran, and Russia, where independent journalism is all but dead, self-censorship and toad-eating are rife.

When Bots and Users Meet: Automated Manipulation and the New Culture of Online Suspicion

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Yoav Halperin
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Thematic Analysis ◽  
Public Awareness ◽  
National Elections ◽  
New Techniques ◽  
Discussion Threads ◽  
Online Exchanges ◽  
Media Environments ◽  
Facebook Pages

This article examines the growing public awareness of deceptive online campaigns where automated networks of social media bots are deployed to manipulate public opinion, disrupt debates, and stoke intercommunal strife. Drawing on a grounded thematic analysis of discussion threads that appeared on Israeli politicians’ Facebook pages during the lead-up to Israel’s national elections in April 2019, I argue that users’ frequent allusions and reactions to the presence of suspected manipulative agents allow these users to negotiate, challenge, and raise competing claims regarding whether certain prominent voices on social media are reflective of actual public opinion. As such, this article contributes to the emerging body of literature about online manipulation, which in recent years has focused mostly on examining the nature and scope of deceptive bot campaigns around the globe and on devising new techniques for detecting and countering the activities of fake social media accounts. The present investigation, in contrast, seeks to shift attention away from bots themselves and toward their intended targets: ordinary users and their discourse. In so doing, it aims to contribute to and expand the study of how automated manipulation is shaping contemporary social media environments by asking: What do ordinary users have to say about the deployment of political bots? How does users’ growing awareness of deceptive bot campaigns inform their interpretations of their own online experiences? And how do users leverage claims about bot activity in online exchanges with others to advance their political agendas?

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.

Post-Truths and Fake News in Disinformation Contexts

2020 ◽  
pp. 306-320
Author(s):  
Maria del Mar Ramirez-Alvarado
Keyword(s):  
Social Media ◽  
Public Opinion ◽  
Fake News ◽  
Personal Beliefs ◽  
General Introduction ◽  
News Stories ◽  
News Sources ◽  
Emotional Appeals ◽  
Theoretical Reflection

This chapter analyses the concept of post-truth related to the circumstances in which objective facts are less influential in the formation of public opinion than emotional appeals and personal beliefs, and the subsequent projection of this phenomenon in social media, as various studies have demonstrated that some fake news stories generate more engagement from users than vetted reporting from reliable news sources. This will start from a general introduction and an associated theoretical reflection, and then focus on the case of Venezuela and its recent historical circumstances in order to analyze how fake news circulates in this country stimulated by a context of widespread disinformation.

scholarly journals The COVID States Project #18: Fake news on Twitter

2021 ◽  
Author(s):  
David Lazer ◽  
Damian J. Ruck ◽  
Alexi Quintana ◽  
Sarah Shugars ◽  
Kenneth Joseph ◽  
...  
Keyword(s):  
Social Media ◽  
Real Time ◽  
Economic Crisis ◽  
Classification System ◽  
Direct Costs ◽  
Fake News ◽  
Cleaning Product ◽  
Freedom Of Movement ◽  
News Websites ◽  
2016 Election

Social media acts as a conduit for fake news websites, where we define fake news as information that mirrors legitimate news in form, but “lacks the news media’s editorial norms and processes for ensuring the accuracy and credibility of information.”4 During the 2016 election, for example, many researchers and journalists alike failed to track the weaponization of misinformation on social media, leaving them to retroactively discover which demographics had been most active in sharing fake news after the election had taken place. It is important to understand in real time which parts of the population are sharing fake news on Twitter.The COVID-19 pandemic has been a once-in-a-generation disruption for Americans. According to the CDC, by October 2020, there were over 8 million cases of COVID-19 and over 200,000 deaths.5 The consequences for Americans have been wide-ranging, from coping with staggering numbers of illnesses and deaths, to restrictions on freedom of movement, to mass unemployment and economic crisis. There has been a great deal of confusion and misinformation surrounding COVID-19 − a so-called Infodemic6 − with much of it occurring online. The BBC documented the direct costs of COVID-19 misinformation, which include alcohol and cleaning product poisonings, assault, property damage and heightened racism.7In our panel, between January 1st and September 30th, 2020, the vast majority of shared URLs from COVID-19 tweets are either from known, reputable domains (60%), or domains with unknown quality (38.9%). URLs from domains that publish fake news only comprise 1.1% of the URLs from COVID-19 tweets. However, this is likely an underestimate because if we include web domains rated as “orange” in our fake news classification system, the percentage of shared fake news URLs increases to 1.8%.

scholarly journals Ratioing the President: An exploration of public engagement with Obama and Trump on Twitter

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0248880
Author(s):  
Joshua R. Minot ◽  
Michael V. Arnold ◽  
Thayer Alshaabi ◽  
Christopher M. Danforth ◽  
Peter Sheridan Dodds
Keyword(s):  
United States ◽  
Social Media ◽  
Public Engagement ◽  
Political Engagement ◽  
The United States ◽  
Fake News ◽  
Donald Trump ◽  
The Past ◽  
2016 Election ◽  
Use Of Social Media

The past decade has witnessed a marked increase in the use of social media by politicians, most notably exemplified by the 45th President of the United States (POTUS), Donald Trump. On Twitter, POTUS messages consistently attract high levels of engagement as measured by likes, retweets, and replies. Here, we quantify the balance of these activities, also known as “ratios”, and study their dynamics as a proxy for collective political engagement in response to presidential communications. We find that raw activity counts increase during the period leading up to the 2016 election, accompanied by a regime change in the ratio of retweets-to-replies connected to the transition between campaigning and governing. For the Trump account, we find words related to fake news and the Mueller inquiry are more common in tweets with a high number of replies relative to retweets. Finally, we find that Barack Obama consistently received a higher retweet-to-reply ratio than Donald Trump. These results suggest Trump’s Twitter posts are more often controversial and subject to enduring engagement as a given news cycle unfolds.

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