Sharing, commenting, and reacting to Danish misinformation: A case study of cognitive attraction on Facebook
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References
- Abu Arqoub, O., Elega, A. A., Efe Özad, B., Dwikat, H., & Oloyede, F. A. (2020). Mapping the scholarship of fake news research: A systematic review.
Journalism Practice ,16 (1), 56–86. https://doi.org/10.1080/17512786.2020.1805791 - Acerbi, A. (2016). A cultural evolution approach to digital media.
Frontiers in Human Neuroscience ,10 . https://doi.org/10.3389/fnhum.2016.00636 - Acerbi, A. (2019). Cognitive attraction and online misinformation.
Palgrave Communications ,5 (1), 15. https://doi.org/10.1057/s41599-019-0224-y - Acerbi, A. (2021).
From storytelling to Facebook: Content biases when retelling or sharing a story [Preprint]. Open Science Framework. https://doi.org/10.31219/osf.io/br56y - Altay, S., Hacquin, A.-S., & Mercier, H. (2022). Why do so few people share fake news? It hurts their reputation.
New Media & Society ,24 (6), 1303–1324. https://doi.org/10.1177/1461444820969893 - Apenteng, B. A., Ekpo, I. B., Mutiso, F. M., Akowuah, E. A., & Opoku, S. T. (2020). Examining the relationship between social media engagement and hospital revenue.
Health Marketing Quarterly ,37 (1), 10–21. https://doi.org/10.1080/07359683.2020.1713575 - Bak, P. de P., Walter, J. G., & Bechmann, A. (2022). Digital false information at scale in the European Union: Current state of research in various disciplines, and future directions.
New Media & Society ,25 (10), 2800–2819. https://doi.org/10.1177/14614448221122146 - Bebbington, K., MacLeod, C., Ellison, T. M., & Fay, N. (2017). The sky is falling: Evidence of a negativity bias in the social transmission of information.
Evolution and Human Behavior ,38 (1), 92–101. https://doi.org/10.1016/j.evolhumbehav.2016.07.004 - Berger, J., & Milkman, K. L. (2010).
Social transmission, emotion, and the virality of online content [Marketing Science Institute Working Paper Series 2010, Report No. 10-114]. https://thearf-org-unified-admin.s3.amazonaws.com/MSI/2020/06/MSI_Report_10-114.pdf - Berriche, M., & Altay, S. (2020). Internet users engage more with phatic posts than with health misinformation on Facebook.
Palgrave Communications ,6 (1), Article 71. https://doi.org/10.1057/s41599-020-0452-1 - Blaine, T., & Boyer, P. (2018). Origins of sinister rumors: A preference for threat-related material in the supply and demand of information.
Evolution and Human Behavior ,39 (1), 67–75. https://doi.org/10.1016/j.evolhumbehav.2017.10.001 - Boyer, P., & Parren, N. (2015). Threat-related information suggests competence: A possible factor in the spread of rumors.
PLOS ONE ,10 (6), e0128421. https://doi.org/10.1371/journal.pone.0128421 - Brady, W. J., Gantman, A. P., & Van Bavel, J. J. (2020). Attentional capture helps explain why moral and emotional content go viral.
Journal of Experimental Psychology: General ,149 (4), 746–756. https://doi.org/10.1037/xge0000673 - Bruni, L., Francalanci, C., & Giacomazzi, P. (2012). The role of multimedia content in determining the virality of social media information.
Information ,3 (3), 278–289. https://doi.org/10.3390/info3030278 - Bucher, T., & Helmond, A. (2018). The affordances of social media platforms. In
The SAGE handbook of social media . Sage. https://doi.org/10.4135/9781473984066 - Bürkner, P.-C. (2017). brms: An R package for bayesian multilevel models using Stan.
Journal of Statistical Software ,80 (1). https://doi.org/10.18637/jss.v080.i01 - De León, E., & Trilling, D. (2021). A sadness bias in political news sharing? The role of discrete emotions in the engagement and dissemination of political news on Facebook.
Social Media + Society ,7 (4), 205630512110597. https://doi.org/10.1177/20563051211059710 - de Oliveira, D. V. B., & Albuquerque, U. P. (2021). Cultural evolution and digital media: Diffusion of fake news about COVID-19 on Twitter.
SN Computer Science ,2 (6), 430. https://doi.org/10.1007/s42979-021-00836-w - Derczynski, L., Albert-Lindqvist, T. O., Bendsen, M. V., Inie, N., Pedersen, V. D., & Pedersen, J. E. (2019, October 31). Misinformation on Twitter during the Danish national election: A case study.
Proceedings of the Conference for Truth and Trust Online 2019 . https://doi.org/10.36370/tto.2019.16 - DR Analyse. (2024).
Medieudviklingen 2023 . Danmarks Radio (DR). https://tinyurl.com/34zwmy44 - Dunbar, R. I. M. (2004). Gossip in evolutionary perspective.
Review of General Psychology ,8 (2), 100–110. https://doi.org/10.1037/1089-2680.8.2.100 - Dunbar, R. I. M. (2009). The social brain hypothesis and its implications for social evolution.
Annals of Human Biology ,36 (5), 562–572. https://doi.org/10.1080/03014460902960289 - Ferrara, E., & Yang, Z. (2015). Quantifying the effect of sentiment on information diffusion in social media.
PeerJ Computer Science ,1 , e26. https://doi.org/10.7717/peerj-cs.26 - Fine, J. A., & Hunt, M. F. (2023). Negativity and elite message diffusion on social media.
Political Behavior ,45 (3), 955–973. https://doi.org/10.1007/s11109-021-09740-8 - Funke, D. (2020).
PolitiFact | fact-checking ‘Plandemic’: A documentary full of false conspiracy theories about the coronavirus . https://www.politifact.com/article/2020/may/08/fact-checking-plandemic-documentary-full-false-con/ - Gabry, J., & Mahr, T. (2022).
bayesplot: Plotting for bayesian models. https://mc-stan.org/bayesplot/ - Gelman, A., Goodrich, B., Gabry, J., & Vehtari, A. (2019). R-squared for bayesian regression models.
The American Statistician ,73 (3), 307–309. https://doi.org/10.1080/00031305.2018.1549100 - Goodrich, K. (2011). Anarchy of effects? Exploring attention to online advertising and multiple outcomes.
Psychology & Marketing ,28 (4), 417–440. https://doi.org/10.1002/mar.20371 - Greene, W. H. (2003).
Econometric analysis (5th ed). Prentice Hall. - Gross, J., & Von Wangenheim, F. (2022). Influencer marketing on Instagram: Empirical research on social media engagement with sponsored posts.
Journal of Interactive Advertising ,22 (3), 289–310. https://doi.org/10.1080/15252019.2022.2123724 - Hartig, F. (2024).
Installing, loading and citing the package [Computer software]. https://cran.r-project.org/web/packages/DHARMa/vignettes/DHARMa.html - Hewstone, M., Rubin, M., & Willis, H. (2002). Intergroup bias.
Annual Review of Psychology ,53 (1), 575–604. https://doi.org/10.1146/annurev.psych.53.100901.135109 - Hilbe, J. M. (2011).
Negative binomial regression (2nd ed.). Cambridge University Press. https://doi.org/10.1017/CBO9780511973420 - Kendal, R. L., Boogert, N. J., Rendell, L., Laland, K. N., Webster, M., & Jones, P. L. (2018). Social learning strategies: Bridge-building between fields.
Trends in Cognitive Sciences ,22 (7), 651–665. https://doi.org/10.1016/j.tics.2018.04.003 - King, K. K., & Wang, B. (2023). Diffusion of real versus misinformation during a crisis event: A big data-driven approach.
International Journal of Information Management ,71 , 102390. https://doi.org/10.1016/j.ijinfomgt.2021.102390 - Li, Y., & Xie, Y. (2020). Is a picture worth a thousand words? An empirical study of image content and social media engagement – Yiyi Li, Ying Xie, 2020.
Journal of Marketing Research . https://journals.sagepub.com/doi/full/10.1177/0022243719881113?utm_source=chatgpt.com - López-García, X., Costa-Sánchez, C., & Vizoso, Á. (2021). Journalistic fact-checking of information in pandemic: Stakeholders, hoaxes, and strategies to fight disinformation during the Covid-19 crisis in Spain.
International Journal of Environmental Research and Public Health ,18 (3), 1227. https://doi.org/10.3390/ijerph18031227 - Lüdecke, D., Ben-Shachar, M., Patil, I., Waggoner, P., & Makowski, D. (2021). performance: An R Package for Assessment, Comparison and Testing of Statistical Models.
Journal of Open Source Software ,6 (60), 3139. https://doi.org/10.21105/joss.03139 - Luo, H., Meng, X., Zhao, Y., & Cai, M. (2023). Exploring the impact of sentiment on multi-dimensional information dissemination using COVID-19 data in China.
Computers in Human Behavior ,144 , 107733. https://doi.org/10.1016/j.chb.2023.107733 - Lyons, A., & Kashima, Y. (2001). The reproduction of culture: Communication processes tend to maintain cultural stereotypes.
Social Cognition ,19 (3), 372–394. https://doi.org/10.1521/soco.19.3.372.21470 - Martin, D., Cunningham, S. J., Hutchison, J., Slessor, G., & Smith, K. (2017). How societal stereotypes might form and evolve via cumulative cultural evolution.
Social and Personality Psychology Compass ,11 (9), e12338. https://doi.org/10.1111/spc3.12338 - Marwick, A. E., & boyd, d. (2011). I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience.
New Media & Society ,13 (1), 114–133. https://doi.org/10.1177/1461444810365313 - McGuigan, N., & Cubillo, M. (2013). Information transmission in young children: When social information is more important than nonsocial information.
The Journal of Genetic Psychology ,174 (6), 605–619. https://doi.org/10.1080/00221325.2012.749833 - Mesoudi, A., Whiten, A., & Dunbar, R. (2006). A bias for social information in human cultural transmission.
British Journal of Psychology ,97 (3), 405–423. https://doi.org/10.1348/000712605X85871 - Metzler, H., & Garcia, D. (2022).
Social drivers and algorithmic mechanisms on digital media [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/cxa9u - Metzler, H., & Garcia, D. (2023). Social drivers and algorithmic mechanisms on digital media.
Perspectives on Psychological Science ,19 (5), 735–748. https://doi.org/10.1177/17456916231185057 - Morin, O., & Acerbi, A. (2017). Birth of the cool: A two-centuries decline in emotional expression in Anglophone fiction.
Cognition and Emotion ,31 (8), 1663–1675. https://doi.org/10.1080/02699931.2016.1260528 - Mousavi, M., Davulcu, H., Ahmadi, M., Axelrod, R., Davis, R., & Atran, S. (2022). Effective messaging on social media: What makes online content go viral?
Proceedings of the ACM Web Conference 2022 , 2957–2966. https://doi.org/10.1145/3485447.3512016 - Nairne, J. S., Thompson, S. R., & Pandeirada, J. N. S. (2007). Adaptive memory: Survival processing enhances retention.
Journal of Experimental Psychology: Learning, Memory, and Cognition ,33 (2), 263–273. https://doi.org/10.1037/0278-7393.33.2.263 - Newman, N., Fletcher, R., Robertson, C. T., Ross Arguedas, A., & Nielsen, R. K. (2024).
Reuters Institute digital news report 2024 . Reuters Institute for the Study of Journalism, University of Oxford. https://doi.org/10.60625/RISJ-VY6N-4V57 - Nissen, I. A., Walter, J. G., Charquero-Ballester, M., & Bechmann, A. (2022). Digital infrastructures of COVID-19 misinformation: A new conceptual and analytical perspective on fact-checking.
Digital Journalism ,10 (5), 738–760. https://doi.org/10.1080/21670811.2022.2026795 - OSF. (2023, October 16).
Sharing, commenting and reacting to Danish Misinformation: A Case Study of Cognitive Attraction on Facebook [Project]. https://osf.io/dqrky/?view_only=6680bf5c343344f48ead45fe7314af0e - Pieters, R., & Wedel, M. (2004). Attention capture and transfer in advertising: Brand, pictorial, and text-size effects.
Journal of Marketing ,68 (2), 36–50. https://doi.org/10.1509/jmkg.68.2.36.27794 - R Core Team. (2023).
R: A language and environment for statistical computing . https://www.R-project.org/ - Rathje, S., Robertson, C., Brady, W. J., & Van Bavel, J. J. (2024). People think that social media platforms do (but should not) amplify divisive content.
Perspectives on Psychological Science ,19 (5), 781–795. https://doi.org/10.1177/17456916231190392 - Rozin, P., & Royzman, E. B. (2001). Negativity bias, negativity dominance, and contagion.
Personality and Social Psychology Review ,5 (4), 296–320. https://doi.org/10.1207/S15327957PSPR0504_2 - Scheffer, M., van de Leemput, I., Weinans, E., & Bollen, J. (2021). The rise and fall of rationality in language.
Proceedings of the National Academy of Sciences ,118 (51), e2107848118. https://doi.org/10.1073/pnas.2107848118 - Schöne, J. P., Parkinson, B., & Goldenberg, A. (2021). Negativity spreads more than positivity on Twitter after both positive and negative political situations.
Affective Science ,2 (4), 379–390. https://doi.org/10.1007/s42761-021-00057-7 - Song, X., Petrak, J., Jiang, Y., Singh, I., Maynard, D., & Bontcheva, K. (2021). Classification aware neural topic model and its application on a new COVID-19 disinformation corpus.
PLOS ONE ,16 (2), e0247086. https://doi.org/10.1371/journal.pone.0247086 - Statista. (2023).
Most popular social networks worldwide as of January 2023, ranked by number of monthly active users . https://www.statista.com/statistics/272014/global-social-networks-ranked-by-number-of-users/ - Statista. (2024).
Daily social media usage worldwide . https://www.statista.com/statistics/433871/daily-social-media-usage-worldwide/ - Stieglitz, S., & Dang-Xuan, L. (2013). Emotions and information diffusion in social media—Sentiment of microblogs and sharing behavior.
Journal of Management Information Systems ,29 (4), 217–248. https://doi.org/10.2753/MIS0742-1222290408 - Stubbersfield, J. M. (2022). Content biases in three phases of cultural transmission: A review.
Culture and Evolution ,19 (1), 41–60. https://doi.org/10.1556/2055.2022.00024 - Stubbersfield, J. M. (2025). Content-based learning biases. In T. Shackelford (Ed.),
Encyclopedia of religious psychology and behavior (pp. 1–16). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-38971-9_134-1 - Stubbersfield, J. M., Flynn, E. G., & Tehrani, J. J. (2017). Cognitive evolution and the transmission of popular narratives: A literature review and application to urban legends.
Evolutionary Studies in Imaginative Culture ,1 (1), 121–136. https://doi.org/10.26613/esic.1.1.20 - Stubbersfield, J. M., Tehrani, J. J., & Flynn, E. G. (2015). Serial killers, spiders and cybersex: Social and survival information bias in the transmission of urban legends.
British Journal of Psychology ,106 (2), 288–307. https://doi.org/10.1111/bjop.12073 - TjekDet. (2020, August 4).
Arbejdsproces og etisk regelsæt [Work process and ethical code ]. Tjekdet. https://www.tjekdet.dk/arbejdsproces-og-etisk-regelsaet - Tsugawa, S., & Ohsaki, H. (2015). Negative messages spread rapidly and widely on social media.
Proceedings of the 2015 ACM on Conference on Online Social Networks , 151–160. https://doi.org/10.1145/2817946.2817962 - Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online.
Science ,359 (6380), 1146–1151. https://doi.org/10.1126/science.aap9559 - Warrens, M. J. (2015). Five Ways to Look at Cohen’s Kappa.
Journal of Psychology & Psychotherapy ,5 (4), 1000197. https://doi.org/10.4172/2161-0487.1000197 - WHO. (2020).
Infodemic . http://www.who.int/westernpacific/health-topics/infodemic - Youngblood, M., Stubbersfield, J. M., Morin, O., Glassman, R., & Acerbi, A. (2023). Negativity bias in the spread of voter fraud conspiracy theory tweets during the 2020 US election.
Humanities and Social Sciences Communications ,10 (1), 573. https://doi.org/10.1057/s41599-023-02106-x
Language: English
Page range: 55 - 75
Published on: Apr 12, 2025
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