Rather than framing disinformation as false facts which can be countered by true facts, we propose a model of disinformation as narrative by tracing three case studies of successful disinformation ...
Disinformation and grievance narratives
Synthese - Disinformation is often defined as misleading content intended to instill false beliefs. But this definition is too narrow. We need to focus instead on its broader epistemic effects....
How People Weave Online Information Into Pseudoknowledge
Misinformation has found a new natural habitat in the digital age. Thousands of forums, blogs, and alternative news sources amplify fake news and inaccurate information to such a degree that it impacts our collective intelligence. Researchers and policy makers are troubled by misinformation because it is presumed to energize or even carry false narratives that can motivate poor decision-making and dangerous behaviors. Yet, while a growing body of research has focused on how viral misinformation spreads, little work has examined how false narratives are in fact constructed. In this study, we move beyond contagion inspired approaches to examine how people construct a false narrative. We apply prior work in cognitive science on narrative understanding to illustrate how the narrative changes over time and in response to social dynamics, and examine how forum participants draw upon a diverse set of online sources to substantiate the narrative. We find that the narrative is based primarily on reinterpretations of conventional and scholarly sources, and then used to provide an alternate account of unfolding events. We conclude that the link between misinformation, conventional knowledge, and false narratives is more complex than is often presumed, and advocate for a more direct study of this relationship.
Debunking: A Meta-Analysis of the Psychological Efficacy of Messages Countering Misinformation
This meta-analysis investigated the factors underlying effective messages to counter attitudes and beliefs based on misinformation. Because misinformation can lead to poor decisions about consequential matters and is persistent and difficult to correct, debunking it is an important scientific and public-policy goal. This meta-analysis ( k = 52, N = 6,878) revealed large effects for presenting misinformation ( ds = 2.41–3.08), debunking ( ds = 1.14–1.33), and the persistence of misinformation in the face of debunking ( ds = 0.75–1.06). Persistence was stronger and the debunking effect was weaker when audiences generated reasons in support of the initial misinformation. A detailed debunking message correlated positively with the debunking effect. Surprisingly, however, a detailed debunking message also correlated positively with the misinformation-persistence effect.
Disinformation and grievance narratives
Disinformation is often defined as misleading content intended to instill false beliefs. But this definition is too narrow. We need to focus instead on its broader epistemic effects. Indeed, some disinformation campaigns rely not on sharing falsehoods but on spreading what I call grievance narratives. These narratives exploit the (real or imagined) grievances of a community and frame them as signs of a deeper systemic problem, typically instigated by a powerful and hostile group. In this way, they legitimize and amplify aversive emotions and foster a negative orientation toward the world, one in which emotions like resentment or indignation feel continuously warranted. Now, grievance narratives are particularly harmful because they epistemically isolate their targeted audience. In short, they undermine the network of information sources that a community can rely on and, as such, they obstruct access to epistemic goods, such as knowledge and understanding. This stems from a key feature of these narratives: namely, they polarize the world between those who recognize the forces responsible for the community’s suffering and those who don’t. The latter are portrayed as not merely mistaken, but as either hostile or complicit with those to blame. In this way, grievance narratives systematically foreclose any alternative explanation of the community’s experiences, leaving them with little more than a single narrative to trust.
(PDF) Post-truth and Disinformation: Using discourse analysis to understand the creation of emotional and rival narratives in Brexit
PDF | The present research explores the concept of post-truth and disinformation in regard to Brexit. It is a qualitative and exploratory investigation.... | Find, read and cite all the research you need on ResearchGate
Verification Handbook | DataJournalism.com
This book equips journalists with the knowledge to investigate on disinformation and media manipulation.
Election Disinformation in Different Languages is a Big Problem in the U.S.
And it’s driving a wedge between voters in non-English communities Mis- and disinformation about elections predate the endless scroll of modern social media services. [1] Yet easy access to online information channels and amplification tools enable false narratives to spread at a massive scale. When false narratives are combined with data voids and unique cultural […]
Why Storytelling Matters When Changing Company Culture
A conversation with the University of Utah’s Jay Barney about how leaders who successfully drive cultural change communicate through authentic, compelling stories.
Elena Rossini on GoToSocial ⁂ (@elena@aseachange.com)
[3 media attachments] Dear friends, Please gather around for a long post about #WSocial and how they are responding to critiques. I have noticed a trend: W Social leaders and staunch supporters are describing any critical posts about the company as "targeted disinformation." Its CEO said they will soon have a technical solution in place for this. Oh?!? 🔗: https://mu.social/profile/anna.wsocial.eu/post/3mtqufy6g4s2r I suppose the "targeted disinformation" claims are about recent posts by the likes of me and @pallenberg about troubling hate speech that is allowed on W Social. Claims backed by hard evidence, in the form of screenshots and video captures. (I am increasingly doing screen recordings of problematic posts and interactions by W Social people because they have a tendency to delete evidence - like an infamous comment on a video by the Instutute for Remigration). ⬇️ ⬇️ ⬇️ Discrediting sources, renaming evidence as "disinformation" and creating a victim narrative has a long, storied history. ⬆️ ⬆️ ⬆️ But I'm digressing. I speak up about W Social because: - Mainstream media runs PR fluff about them; - Horrid hate speech on the platform is completely unmoderated. W Social is currently showing the limits of free speech absolutism. Its CEO wrote: "We don’t need W to become another echo chamber." Reminds you of something? Atmosphere user @echna.bsky.social astutely remarked that "W Social is on an X speedrun, without ever having been like Twitter." 🔗: https://mu.social/profile/echna.bsky.social/post/3mtqlknzork2t Bluesky, #Blacksky, and #Northsky have mechanisms in place to report hate speech - and I am super thankful for that. As of today, I cannot report to W Social posts by their users that contain hate speech. The W Social moderation list's only purpose is to make a distinction between verified users and bots. Compare it with Blacksky's moderation list and be amazed (see screenshots). What's the big deal about the lack of content moder…
How Social Media Rewards Misinformation
A majority of false stories are spread by a small number of frequent users, suggests a new study co-authored by Yale SOM’s Gizem Ceylan. But they can be taught to change their ways.
Deep Storytelling: Collective Sensemaking and Layers of Meaning in U.S. Elections
Misinformation and disinformation about elections remain pressing concerns for researchers, policymakers, and the public. Critics, however, argue that fears surrounding these issues are exaggerated due to a lack of evidence of impact. This debate highlights the challenges inherent in assessing the impacts of misinformation, as the drivers of false and misleading content often exist in the context of a specific claim. To address this issue, we examined false and misleading information surrounding the 2020 and 2022 U.S. national elections, focusing on the contextual features of online conversations that fueled various rumors. We developed two qualitative codebooks, creating the second after realizing that the first, which labeled individual tweets, failed to capture broader rumoring dynamics. By integrating multi-layered qualitative coding with thematic analysis and quantitative visualizations, we show how influencers, political elites, and audiences collaboratively told deep stories from 2020 through 2022. As these stories were told, audiences interpreted events in 2022 through the lens of the 2020 story, guided by influencers' cues, leading to an evolution in storytelling style between the two election cycles. This ongoing performance was tailored to align with the incentive structures, affordances, and attention economy of social media. We combine deep stories with theories of collective sensemaking and rumoring, creating a framework to better assess the contextual features surrounding false and misleading information.
Political disinformation concentrates in repeated claims across media
The prevalence and dynamics of disinformation remain contentious, partly because measures have relied on posts containing URLs from untrustworthy sources. We move beyond this by detecting disinformation in text and across posts. Using retrieval-augmented generation, we match six million Facebook, Instagram, and X posts by politicians from the United States, United Kingdom, and Germany, and two million articles from news outlets to fact-checked claims. We show that disinformation is concentrated in a small number of combinations of policy issues and parties and that just over hundred distinct claims account for around half of all disinformation across the three countries. They often appear first on a single platform, later on multiple, and subsequently in news coverage before being fact-checked. These findings suggest that disinformation is concentrated in a narrow segment of political communication, potentially creating repeated exposure that may shape the terms of public debate through both social and news media.
Fact-Checks Can Help Inoculate LLMs Against Disinformation
Large language models (LLMs) have become the first source millions consult when evaluating political claims, yet they were trained on an open internet that state-sponsored disinformation operations have been designed to pollute. We audit four frontier models across 2,268 responses to 63 fabrications from eight documented influence operations and find that even a single published fact-check can shift a model from hedging about a fabrication to rejecting it outright. Overall, models correctly rejected only 81% of fabrications while repeating disinformation in 3% of cases. Critically, the remaining 16% of responses would have left users unable to determine whether an fabricated claims were true or false. Fact-checks may present an avenue for addressing this vulnerability. Narratives which had been debunked by at least one IFCN certified fact-checking organization were correctly rejected as disinformation 93% of the time compared to just 76% of the time for unchecked narratives. Exploratory analyses suggest that this mechanism operates through training data, with models echoing the specific vocabulary of published corrections when available during their training windows. We conclude by discussing how fact-checks designed for human audiences appear to serve as effective protection for LLMs, converting both model uncertainty and outright disinformation into definitive rejections
The five biggest challenges facing misinformation researchers
We're getting the social media crisis wrong
The bigger problem isn't disinformation. It's degraded democratic publics
We're getting the social media crisis wrong
The bigger problem isn't disinformation. It's degraded democratic publics