Sharing, commenting, and reacting to Danish misinformation
A case study of cognitive attraction on Facebook
Datos Bibliográficos
| ID | 6443897 |
|---|---|
| Autores | Petra De Place Bak (0000-0003-3728-7845, Aarhus University), Ethan Weed (0000-0002-3921-9101, Aarhus University) |
| Año | 2025 |
| Volumen | 46 |
| Número | 1 |
| Páginas | 55-75 |
| Fecha de publicación | 2025-01-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Nordicom review/NORDICOM review (JOURNAL) |
| Identificadores de la revista | ISSN: 1403-1108 • E-ISSN: 2001-5119 |
| Editorial | De Gruyter Open (PUBLISHER • PL) |
| DOI | 10.2478/nor-2025-0003 |
| OpenAlex | W4409382930 |
| Idioma | EN |
| Referencias citadas | 58 |
Social media facilitate a competition for users’ limited attention by bringing various content together, from health advice to entertainment, and from updates from loved ones to misinformation. Especially misinformation has raised societal concern. We evaluated the influence of visual material and cognitive factors of attraction, specifically valenced sentiment, threat-related, intergroup-related, and social information, on engagement scores (i.e., shares, comments, and reactions). We analysed 356 misleading Danish Facebook posts sampled through the fact-checking association TjekDet’s “entirely or partly false” web page by fitting a Bayesian zero-inflated negative binomial regression model. The study showed that videos and images were exceptionally strong predictors of engagement, especially shares. Positivity, negativity, and intergroup-related information also increased engagement, but social information and threat-related information reduced it. Our findings suggest that in a highly competitive online environment, some content biases are stronger than others. Finally, we discuss the potential moderators of their effect such as the users’ reputation management strategies
Attraction · Cognition · Computer security · Danish · Linguistics · Misinformation · Computer Science · Digital Communication and Language · Misinformation and Its Impacts · Psychology · Social Media and Politics · Social Psychology
Origins of sinister rumors
Negative Binomial Regression
R-squared for Bayesian Regression Models
Performance
Social Learning Strategies
Attention Capture and Transfer in Advertising
The Affordances of Social Media Platforms
Negativity Bias, Negativity Dominance, and Contagion
BRMS
Digital Infrastructures of Covid-19 Misinformation
Social Drivers and Algorithmic Mechanisms on Digital Media
People Think That Social Media Platforms Do (but Should Not) Amplify Divisive Content
Exploring the impact of sentiment on multi-dimensional information dissemination using Covid-19 data in China
Negativity bias in the spread of voter fraud conspiracy theory tweets during the 2020 US election
Internet users engage more with phatic posts than with health misinformation on Facebook
Content biases in three phases of cultural transmission
Mapping the Scholarship of Fake News Research
Journalistic Fact-Checking of Information in Pandemic
The social brain hypothesis and its implications for social evolution
Digital false information at scale in the European Union
Why do so few people share fake news? It hurts their reputation
The sky is falling
Negativity and Elite Message Diffusion on Social Media
Gossip in Evolutionary Perspective
I tweet honestly, I tweet passionately
Intergroup Bias
A bias for social information in human cultural transmission
Serial killers, spiders and cybersex
A Sadness Bias in Political News Sharing? The Role of Discrete Emotions in the Engagement and Dissemination of Political News on Facebook
| Velocidad de citación | historical |
|---|---|
| Altamente citado | No |