scholarly journals Leadership in a post-truth era: A new narrative disorder?

Leadership ◽  
2019 ◽  
Vol 15 (2) ◽  
pp. 135-151 ◽  
Author(s):  
Hamid Foroughi ◽  
Yiannis Gabriel ◽  
Marianna Fotaki
Keyword(s):  
Social Media ◽  
Economic Crisis ◽  
Fake News ◽  
Special Issue ◽  
Conspiracy Theories ◽  
Digital Revolution ◽  
Counter Narrative ◽  
Counter Narratives ◽  
Different Types ◽  
Historical Periods

This essay, and the special issue it introduces, seeks to explore leadership in a post-truth age, focusing in particular on the types of narratives and counter-narratives that characterize it and at times dominate it. We first examine the factors that are often held responsible for the rise of post-truth in politics, including the rise of relativist and postmodernist ideas, dishonest leaders and bullshit artists, the digital revolution and social media, the 2008 economic crisis and collapse of public trust. We develop the idea that different historical periods are characterized by specific narrative ecologies, which, by analogy to natural ecologies, can be viewed as spaces where different types of narrative and counter-narrative emerge, interact, compete, adapt, develop and die. We single out some of the dominant narrative types that characterize post-truth narrative ecologies and highlight the ability of language to ‘do things with words’ that support both the production of ‘fake news’ and a type of narcissistic leadership that thrive in these narrative ecologies. We then examine more widely leadership in post-truth politics focusing on the resurgence of populist and demagogical types along with the narratives that have made these types highly effective in our times. These include nostalgic narratives idealizing a fictional past and conspiracy theories aimed at arousing fears about a dangerous future.

scholarly journals Linguistic drivers of misinformation diffusion on social media during the COVID-19 pandemic

2021 ◽  
Author(s):  
Giandomenico Di Domenico ◽  
Annamaria Tuan ◽  
Marco Visentin
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
New Technologies ◽  
Fake News ◽  
Conspiracy Theories ◽  
Social Media Platform ◽  
The Social ◽  
Media Platform ◽  
Textual Cues ◽  
Twitter Users

AbstractIn the wake of the COVID-19 pandemic, unprecedent amounts of fake news and hoax spread on social media. In particular, conspiracy theories argued on the effect of specific new technologies like 5G and misinformation tarnished the reputation of brands like Huawei. Language plays a crucial role in understanding the motivational determinants of social media users in sharing misinformation, as people extract meaning from information based on their discursive resources and their skillset. In this paper, we analyze textual and non-textual cues from a panel of 4923 tweets containing the hashtags #5G and #Huawei during the first week of May 2020, when several countries were still adopting lockdown measures, to determine whether or not a tweet is retweeted and, if so, how much it is retweeted. Overall, through traditional logistic regression and machine learning, we found different effects of the textual and non-textual cues on the retweeting of a tweet and on its ability to accumulate retweets. In particular, the presence of misinformation plays an interesting role in spreading the tweet on the network. More importantly, the relative influence of the cues suggests that Twitter users actually read a tweet but not necessarily they understand or critically evaluate it before deciding to share it on the social media platform.

scholarly journals Introduction

Pragmatics ◽  
2020 ◽  
Vol 30 (2) ◽  
pp. 169-178
Author(s):  
Korina Giaxoglou ◽  
Marjut Johansson
Keyword(s):  
Social Media ◽  
Research Articles ◽  
Special Issue ◽  
News Consumption ◽  
Different Types ◽  
The Creation ◽  
Changing Practices ◽  
The Individual ◽  
Story Sharing ◽  
Empirical Analyses

Abstract This introduction to the Special Issue on Networked Emotion and Stancetaking summarizes the individual and collective contribution of the included five research articles. We argue for the relevance of discourse-pragmatic theories, methods, and concepts for furnishing cross-disciplinary perspectives into the study of emotion online. Such perspectives are arguably needed in order to clarify the intricate connections between (re)presentations of emotion online and changing practices of news-making and news consumption, story sharing and participation, and public stancetaking in social media and beyond. We propose that empirical analyses of networked practices of stancetaking – epistemic, affective, or narrative – can pinpoint the construction and dissemination of different types of participant positions and stances, including multimodal ones, as well as the creation and uptake of specific frames for interpreting events and crises affectively.

scholarly journals False news around COVID-19 circulated less on Sina Weibo than on Twitter. How to overcome false information?

2020 ◽  
Author(s):  
Cristina Pulido Rodríguez ◽  
Beatriz Villarejo Carballido ◽  
Gisela Redondo-Sama ◽  
Mengna Guo ◽  
Mimar Ramis ◽  
...  
Keyword(s):  
Social Media ◽  
Evidence Based ◽  
World Economic Forum ◽  
Fake News ◽  
Best Interest ◽  
False Information ◽  
Conspiracy Theories ◽  
Sina Weibo ◽  
World Economic ◽  
False News

Since the Coronavirus health emergency was declared, many are the fake news that have circulated around this topic, including rumours, conspiracy theories and myths. According to the World Economic Forum, fake news is one of the threats in today's societies, since this type of information circulates fast and is often inaccurate and misleading. Moreover, fake-news are far more shared than evidence-based news among social media users and thus, this can potentially lead to decisions that do not consider the individual’s best interest. Drawing from this evidence, the present study aims at comparing the type of Tweets and Sina Weibo posts regarding COVID-19 that contain either false or scientific veracious information. To that end 1923 messages from each social media were retrieved, classified and compared. Results show that there is more false news published and shared on Twitter than in Sina Weibo, at the same time science-based evidence is more shared on Twitter than in Weibo but less than false news. This stresses the need to find effective practices to limit the circulation of false information.

Fake News

2018 ◽  
Author(s):  
Bente Kalsnes
Keyword(s):  
Communication Technologies ◽  
Social Motivation ◽  
Research Literature ◽  
Fake News ◽  
False Information ◽  
Conspiracy Theories ◽  
Different Types ◽  
Fact Checking ◽  
Definition Of ◽  
Different Levels

Fake news is not new, but the American presidential election in 2016 placed the phenomenon squarely onto the international agenda. Manipulation, disinformation, falseness, rumors, conspiracy theories—actions and behaviors that are frequently associated with the term—have existed as long as humans have communicated. Nevertheless, new communication technologies have allowed for new ways to produce, distribute, and consume fake news, which makes it harder to differentiate what information to trust. Fake news has typically been studied along four lines: Characterization, creation, circulation, and countering. How to characterize fake news has been a major concern in the research literature, as the definition of the term is disputed. By differentiating between intention and facticity, researchers have attempted to study different types of false information. Creation concerns the production of fake news, often produced with either a financial, political, or social motivation. The circulation of fake news refers to the different ways false information has been disseminated and amplified, often through communication technologies such as social media and search engines. Lastly, countering fake news addresses the multitude of approaches to detect and combat fake news on different levels, from legal, financial, and technical aspects to individuals’ media and information literacy and new fact-checking services.

Cracking Open the News Feed

2021 ◽  
Vol 1 ◽  
Author(s):  
Andy Guess ◽  
Kevin Aslett ◽  
Joshua Tucker ◽  
Richard Bonneau ◽  
Jonathan Nagler
Keyword(s):  
Social Media ◽  
Fake News ◽  
Older Americans ◽  
News Sources ◽  
Older Users ◽  
Different Types ◽  
Supervised Classifiers ◽  
Sharing Patterns ◽  
First Time

In this study, we analyze for the first time newly available engagement data covering millions of web links shared on Facebook to describe how and by which categories of U.S. users different types of news are seen and shared on the platform. We focus on articles from low-credibility news publishers, credible news sources, purveyors of clickbait, and news specifically about politics, which we identify through a combination of curated lists and supervised classifiers. Our results support recent findings that more fake news is shared by older users and conservatives and that both viewing and sharing patterns suggest a preference for ideologically congenial misinformation. We also find that fake news articles related to politics are more popular among older Americans than other types, while the youngest users share relatively more articles with clickbait headlines. Across the platform, however, articles from credible news sources are shared over 5 times more often and viewed over 7 times more often than articles from low-credibility sources. These findings offer important context for researchers studying the spread and consumption of information — including misinformation — on social media.

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.

scholarly journals Early Days of the Novel Coronavirus: Public Response in Social Media during the First Month of the Outbreak

2021 ◽  
Vol 82 ◽  
pp. 159-182
Author(s):  
Maris Kuperjanov ◽  
Keyword(s):  
Social Media ◽  
The Novel ◽  
Fake News ◽  
Conspiracy Theories ◽  
Public Response ◽  
The Public ◽  
The Media ◽  
Media Environments ◽  
Novel Coronavirus ◽  
Flow Of Information

The aim of the article is to give an overview of the first month of the novel coronavirus outbreak and of the public reactions to the news in media comments and social media environments in both local Estonian and global contexts. The pandemic was still ongoing at the time the article was published and, with some modifications and new emphases, vernacular reactions in the media (incl. social media) continued flourishing. During the first month (January 2020), the growing flow of information and rapid escalation of the situation made the topic more noticeable in both the media and social media, and thus provided a fertile basis for jokes and internet memes, legends, fake news, misinformation, conspiracy theories, etc., as was the case with the former bigger epidemics and pandemics. As it has also been observed previously, the consequences of some fake news, misinformation, and conspiracy theories may often be more harmful for society than the disease itself. Several motifs and storylines are universal and surge as similar situations arise both in Estonia and all over the world. The article also presents a selection of more prominent topics and examples of the outbreak from social media environments during the initial phase of international awareness of the novel coronavirus.

scholarly journals Different types of COVID-19 misinformation have different emotional valence on Twitter

2021 ◽  
Vol 8 (2) ◽  
pp. 205395172110412
Author(s):  
Marina Charquero-Ballester ◽  
Jessica G Walter ◽  
Ida A Nissen ◽  
Anja Bechmann
Keyword(s):  
Social Media ◽  
Emotional Expression ◽  
Emotional Valence ◽  
Conspiracy Theories ◽  
Random Subset ◽  
Negative Valence ◽  
Different Types ◽  
Minor Part ◽  
A Minor ◽  
Entire Dataset

The spreading of COVID-19 misinformation on social media could have severe consequences on people's behavior. In this paper, we investigated the emotional expression of misinformation related to the COVID-19 crisis on Twitter and whether emotional valence differed depending on the type of misinformation. We collected 17,463,220 English tweets with 76 COVID-19-related hashtags for March 2020. Using Google Fact Check Explorer API we identified 226 unique COVID-19 false stories for March 2020. These were clustered into six types of misinformation (cures, virus, vaccine, politics, conspiracy theories, and other). Applying the 226 classifiers to the Twitter sample we identified 690,004 tweets. Instead of running the sentiment on all tweets we manually coded a random subset of 100 tweets for each classifier to increase the validity, reducing the dataset to 2,097 tweets. We found that only a minor part of the entire dataset was related to misinformation. Also, misinformation in general does not lean towards a certain emotional valence. However, looking at comparisons of emotional valence for different types of misinformation uncovered that misinformation related to “virus” and “conspiracy” had a more negative valence than “cures,” “vaccine,” “politics,” and “other.” Knowing from existing studies that negative misinformation spreads faster, this demonstrates that filtering for misinformation type is fruitful and indicates that a focus on “virus” and “conspiracy” could be one strategy in combating misinformation. As emotional contexts affect misinformation spreading, the knowledge about emotional valence for different types of misinformation will help to better understand the spreading and consequences of misinformation.

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.

scholarly journals Trumpism and the Dialectic of Neoliberal Reason

2019 ◽  
Vol 17 (02) ◽  
pp. 380-398 ◽  
Author(s):  
David Lebow
Keyword(s):  
Social Media ◽  
Economic Crisis ◽  
Fake News ◽  
Instrumental Reason ◽  
Negative Freedom ◽  
Positive Freedom ◽  
Private Interests ◽  
The World ◽  
Culture Market ◽  
Democratic Norms

Guided by the thesis that fascism was the outcome of a dialectic of instrumental reason, I argue that Trumpism is the result of a dialectic of neoliberal reason. The 2008 crisis revealed that widely distributed consumption could no longer be sustained through escalating debt, as it had been since neoliberalizing reforms in the 1970s. Economic crisis has been interpreted through a culture market in which pseudo-individual consumers choose what hyperreal public they prefer and participate in pseudo-activity through social media. Retreat into insular hyperrealities and hostility to dissonant alternatives reinforce each other in an escalating logic generating partisan incivility and fake news. The de-democratization of the state through subservience to private interests and political dysfunction has combined with the consumer’s uncompromising mentality as a dissatisfied customer to channel politicization into populism. It aggregates negatively through shared dissatisfaction, driving escalating antagonism between technocratic responsibility and populist responsiveness. These escalating economic, cultural, and political contradictions heighten negative “freedom from” restraints while subverting positive “freedom to” relate meaningfully to the world. This intensifies anxieties and receptivity to authoritarianism as a self-defeating escape from neoliberal freedom. Trumpism exploits precarity, corrupts democratic norms, and licenses misdirected aggression. This neoliberal authoritarianism is inverted fascism. Trump’s presidency is more effect than cause.

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