Junk News Research Articles

Facts, values, and the epistemic authority of journalism: How journalists use and define the terms fake news, junk news, misinformation, and disinformation

Abstract In this article, we examine how journalists try to uphold ideals of objectivity, clarity, and epistemic authority when using four overlapping terms: fake news, junk news, misinformation, and disinformation. Drawing on 16 qualitative interviews with journalists in Denmark, our study finds that journalists struggle to convert the ideals of clarity and objectivity into a coherent conceptual practice. Across interviews, journalists disagree on which concepts to use and how to define them, accusing academics of producing too technical definitions, politicians of diluting meaning, and journalistic peers of being insufficiently objective. Drawing on insights from journalism scholarship and rhetorical argumentation theory, we highlight how such disagreements reveal a fundamental tension in journalistic claims to epistemic authority, causing a continuous search for unambiguous terms, which in turn produces the very ambiguity that journalists seek to avoid.

FaNDS: Fake News Detection System using energy flow

Recently, the term “fake news” has been broadly and extensively utilized for disinformation, misinformation, hoaxes, propaganda, satire, rumors, click-bait, and junk news. It has become a serious problem around the world. We present a new system, FaNDS, that detects fake news efficiently. The system is based on several concepts used in some previous works but in a different context. There are two main concepts: an Inconsistency Graph and Energy Flow. The Inconsistency Graph contains news items as nodes and inconsistent opinions between them for edges. Energy Flow assigns each node an initial energy and then some energy is propagated along the edges until the energy distribution on all nodes converges. To illustrate FaNDS we use the original data from the Fake News Challenge (FNC-1). First, the data has to be reconstructed in order to generate the Inconsistency Graph. The graph contains various subgraphs with well-defined shapes that represent different types of connections between the news items. Then the Energy Flow method is applied. The nodes with high energy are the candidates for being fake news. In our experiments, all these were indeed fake news as we checked each using several reliable web sites. We compared FaNDS to several other fake news detection methods and found it to be more sensitive in discovering fake news items.

How to use the Reflexive Control Theory in order to Identify Online Propaganda in the context of Covid-19 Infodemic

In this article I will begin by addressing the very difficult problem of defining and identifying propaganda in the new context of public communication dominated by the Social Media. This task is notoriously challenging because propaganda became a pejorative word which refers to an activity that remains at least partially concealed and hard to distinguish from other types of persuasive communication and became imbedded in the self-legitimating narratives that define the social identity of human communities. However, t he development of Social Media made this task even harder since it relativized even further the distinction between the public and the private sphere and between political and non-political communication. I will argue that we are witnessing a new propaganda wave which goes along with the development of Social Media, and gains its force by using all the major crises that have the potential to intensify the existing political and social conflicts. My investigation will focus on the current crisis generated by the global Covid-19 pandemic, which is, unfortunately, accompanied by a „Covid-19 infodemic”: a very complex and confuse mixture of misinformation and disinformation with traces of accurate information, with fake and junk news, with propaganda, conspiracy theories and so on. Therefore, it is very hard to identify online propaganda that is disseminated on the Social Media and to differentiate it from the other types of misinformation and disinformation that are contained in this mixture. However, I believe that some clear criteria which can be used in the attempt to single out propaganda narratives can be provided by the theory of Reflexive Control formulated by Vladimir Lefebvre (1984) and developed by Corneliu Bjola (2019) in the form of the 4E Funnel Model. The main objective of my paper will be to present this set of criteria and to apply them to some prominent narratives that were disseminated in Romania on Social Media in the context of the Covid-19 pandemic.

Curating Quality? How Twitter’s Timeline Algorithm Treats Different Types of News

This article explores how Twitter’s algorithmic timeline influences exposure to different types of external media. We use an agent-based testing method to compare chronological timelines and algorithmic timelines for a group of Twitter agents that emulated real-world archetypal users. We first find that algorithmic timelines exposed agents to external links at roughly half the rate of chronological timelines. Despite the reduced exposure, the proportional makeup of external links remained fairly stable in terms of source categories (major news brands, local news, new media, etc.). Notably, however, algorithmic timelines slightly increased the proportion of “junk news” websites in the external link exposures. While our descriptive evidence does not fully exonerate Twitter’s algorithm, it does characterize the algorithm as playing a fairly minor, supporting role in shifting media exposure for end users, especially considering upstream factors that create the algorithm’s input—factors such as human behavior, platform incentives, and content moderation. We conclude by contextualizing the algorithm within a complex system consisting of many factors that deserve future research attention.

Types (Disinformation)

Types (Disinformation)

Junk news bubbles modelling the rise and fall of attention in online arenas

In this article, we present a type of media disorder which we call ‘junk news bubbles’ and which derives from the effort invested by online platforms and their users to identify and circulate contents with rising popularity. Such emphasis on trending matters, we claim, can have two detrimental effects on public debates: first, it shortens the amount of time available to discuss each matter and second, it increases the ephemeral concentration of media attention. We provide a formal description of the dynamic of junk news bubbles, through a mathematical exploration of the famous ‘public arenas model’ developed by Hilgartner and Bosk in 1988. Our objective is to describe the dynamics of the junk news bubbles as precisely as possible to facilitate its further investigation with empirical data.

‘COORDINATED INAUTHENTIC BEHAVIOUR’ AND OTHER ONLINE INFLUENCE OPERATIONS IN SOCIAL MEDIA SPACES

Recently, major social media platforms such as Facebook and Twitter have announced efforts to counter "coordinated inauthentic behaviour." However, scholarly research continues to provide evidence that coordinated human and automated accounts covertly seek to undermine and manipulate public debates on these platforms. Given the difficulties in obtaining data from these platforms to study these influence operations, and the significant challenge of identifying covert malinformation operations, further conceptual and methodological innovations are required. This panel brings together a selection of recent studies that advance the methods available for the forensic, mixed-methods, in-depth, and large-scale analysis of inauthentic information operations: Paper 1 investigates the arson disinformation campaign during the 2019-2020 Australian bushfire season. Paper 2 investigates the distribution and content monetisation strategies of junk news sources across a selection of five major social media platforms during the 2019 European Parliament campaign. Paper 3 explores whether Facebook's microtargeting advertising functionality allows political parties to promote conflicting narratives to different groups of people. Paper 4 studies the experience and engagement with malinformation by users of Facebook and WhatsApp, focussing on the current political environment in Brazil.

Delighting and Detesting Engagement: Emotional Politics of Junk News

How do audiences make sense of and interact with political junk news on Facebook? How does the platform’s “emotional architecture” intervene in these sense-making, interactive processes? What kinds of mediated publics emerge on and through Facebook as a result? We study these questions through topic modeling 40,500 junk news articles, quantitatively analyzing their engagement metrics, and a qualitative comment analysis. This exploratory research design allows us to move between levels of public discourse, zooming in from cross-outlet talking points to microsociological processes of meaning-making, interaction, and emotional entrainment taking place within the comment boxes themselves. We propose the concepts of delighting and detesting engagement to illustrate how the interplay between audiences, platform architecture, and political junk news generates a bivalent emotional dynamic that routinely divides posts into highly “loved” and highly “angering.” We argue that high-performing (or in everyday parlance, viral) junk news bring otherwise disparate audience members together and orient their dramatic focus toward objects of collective joy, anger, or concern. In this context, the nature of political junk news is performative as they become resources for emotional signaling and the construction of group identity and shared feeling on social media. The emotions that animate junk news audiences typically refer back to a transpiring social relationship between two political sides. This affectively loaded “us” versus “them” dynamic is both enforced by Facebook’s emotional architecture and made use of by junk news publishers.

Fake News and Related Concepts: Definitions and Recent Research Development

Fake news is an emerging field of research that attracts much attention from academic communities as well as mass media practitioners. However, the concept of fake news is still ambiguous, and the boundary between the definition of fake news and other relative concepts, such as news satire, yellow journalism, junk news, pseudo-news, hoax news, propaganda news, advertorial, false information, fake information, misinformation, disinformation, mal-information, alternative fact, and post-truth is blurred. The present study aims to identify the meanings of fake news and other related concepts, and explore the recent trend of research on them. By searching the journals listed in the Social Sciences Citation Index (SSCI) and Science Citation Index Expanded (SCI-Expanded) database, the present study found 387 articles on fake news. Through analyzing these articles, the present study maps the trend and reveals the highly influential research articles, as well as theories and concepts that are used. The results may provide fundamental insights into the development of research on fake news in recent years.

Junk News Bubbles: Modelling the Rise and Fall of Attention in Online Arenas

In this paper, we present a type of media disorder which we call “junk news bubbles” and which derives from the effort invested by online platforms and their users to identify and share contents with rising popularity. Such emphasis on trending matters, we claim, can have two detrimental effects on public debates: first, it shortens the amount of time available to discuss each matter; second it increases the ephemeral concentration of media attention. We provide a formal description of the dynamic of junk news bubbles, through a mathematical exploration the famous “public arenas model” developed by Hilgartner and Bosk in 1988. Our objective is to describe the dynamics of the junk news bubbles as precisely as possible to facilitate its further investigation with empirical data.

‘Fake news’ as infrastructural uncanny

In this article, we examine how the social disturbance precipitated by ‘fake news’ can be viewed as a kind of infrastructural uncanny. We suggest that the threat of problematic and viral junk news can raise existential questions about the routine circulation, engagement and monetisation of content through the Web and social media. Prompted by the unsettling effects associated with the ‘fake news’ scandal, we propose methodological tactics for exploring (1) the link economy and the ranking of content, (2) the like economy and the metrification of engagement and (3) the tracker economy and the commodification of attention. Rather than focusing on the misleading content of junk news, such tactics surface the infrastructural conditions of their circulation, enabling public interventions and experiments to interrogate, challenge and change their role in reconfiguring relations between different aspects of social, cultural, economic and political life.

Seeking Clarity in a World Infected by COVID-19 and Fake News

The world has been changed irrevocably by the infectious severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes the coronavirus disease 2019 (COVID-19) that was first identified in Wuhan, China in December 2019. COVID-19 affects everyone everywhere. A separate and significant, though not necessarily as infectious, malady affecting many, though not all, individuals worldwide, is “Fake News”, known alternatively as yellow journalism, junk news, pseudo news, false news, alternative facts, hoaxes, misinformation, disinformation, fabricated news, corrupt news, unfathomable nonsense, or outright lies, which are typically based on provably false statements, and are distributed widely through mainstream news media and social media. The opinion piece presents a brief history of COVID-19 and fake news, and existing international efforts to deal with each of these infections, and to encourage critical comments, concepts and ideas.

Disinformation optimised: gaming search engine algorithms to amplify junk news

Disinformation optimised: gaming search engine algorithms to amplify junk news

Sourcing and Automation of Political News and Information over Social Media in the United States, 2016-2018

Social media is an important source of news and information in the United States. But during the 2016 US presidential election, social media platforms emerged as a breeding ground for influence campaigns, conspiracy, and alternative media. Anecdotally, the nature of political news and information evolved over time, but political communication researchers have yet to develop a comprehensive, grounded, internally consistent typology of the types of sources shared. Rather than chasing a definition of what is popularly known as “fake news,” we produce a grounded typology of what users actually shared and apply rigorous coding and content analysis to define the phenomenon. To understand what social media users are sharing, we analyzed large volumes of political conversations that took place on Twitter during the 2016 presidential campaign and the 2018 State of the Union address in the United States. We developed the concept of “junk news,” which refers to sources that deliberately publish misleading, deceptive, or incorrect information packaged as real news. First, we found a 1:1 ratio of junk news to professionally produced news and information shared by users during the US election in 2016, a ratio that had improved by the State of the Union address in 2018. Second, we discovered that amplifier accounts drove a consistently higher proportion of political communication during the presidential election but accounted for only marginal quantities of traffic during the State of the Union address. Finally, we found that some of the most important units of analysis for general political theory—parties, the state, and policy experts—generated only a fraction of the political communication.

The reach of commercially motivated junk news on Facebook.

Commercially motivated junk news–i.e. money-driven, highly shareable clickbait with low journalistic production standards–constitutes a vast and largely unexplored news media ecosystem. Using publicly available Facebook data, we compared the reach of junk news on Facebook pages in the Netherlands to the reach of Dutch mainstream news on Facebook. During the period 2013–2017 the total number of user interactions with junk news significantly exceeded that with mainstream news. Over 5 Million of the 10 Million Dutch Facebook users have interacted with a junk news post at least once. Junk news Facebook pages also had a significantly stronger increase in the number of user interactions over time than mainstream news. Since the beginning of 2016 the average number of user interactions per junk news post has consistently exceeded the average number of user interactions per mainstream news post.

Sourcing and Automation of Political News and Information During Three European Elections

Voters increasingly rely on social media for news and information about politics. But increasingly, social media has emerged as a fertile soil for deliberately produced misinformation campaigns, conspiracy, and extremist alternative media. How does the sourcing of political news and information define contemporary political communication in different countries in Europe? To understand what users are sharing in their political communication, we analyzed large volumes of political conversation over a major social media platform—in real-time and native languages during campaign periods—for three major European elections. Rather than chasing a definition of what has come to be known as “fake news,” we produce a grounded typology of what users actually shared and apply rigorous coding and content analysis to define the types of sources, compare them in context with known forms of political news and information, and contrast their circulation patterns in France, the United Kingdom, and Germany. Based on this analysis, we offer a definition of “junk news” that refers to deliberately produced misleading, deceptive, and incorrect propaganda purporting to be real news. In the first multilingual, cross-national comparison of junk news sourcing and consumption over social media, we analyze over 4 million tweets from three elections and find that (1) users across Europe shared substantial amounts of junk news in varying qualities and quantities, (2) amplifier accounts drive low to medium levels of traffic and news sharing, and (3) Europeans still share large amounts of professionally produced information from media outlets, but other traditional sources of political information including political parties and government agencies are in decline.

Modernist Literature in the Modern Media Ecology

Modernist Literature in the Modern Media Ecology

FORTRAN Crosscompiler

Recently, the term “fake news” has been broadly and extensively utilized for disinformation, misinformation, hoaxes, propaganda, satire, rumors, click-bait, and junk news. It has become a serious problem around the world. We present a new system, FaNDS, that detects fake news efficiently. The system is based on several concepts used in some previous works but in a different context. There are two main concepts: an Inconsistency Graph and Energy Flow. The Inconsistency Graph contains news items as nodes and inconsistent opinions between them for edges. Energy Flow assigns each node an initial energy and then some energy is propagated along the edges until the energy distribution on all nodes converges. To illustrate FaNDS we use the original data from the Fake News Challenge (FNC-1). First, the data has to be reconstructed in order to generate the Inconsistency Graph. The graph contains various subgraphs with well-defined shapes that represent different types of connections between the news items. Then the Energy Flow method is applied. The nodes with high energy are the candidates for being fake news. In our experiments, all these were indeed fake news as we checked each using several reliable web sites. We compared FaNDS to several other fake news detection methods and found it to be more sensitive in discovering fake news items.