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Fake scientific provenance as a driver for disinformation – Peoples' disinformation behavior in health contexts
Fake scientific provenance as a driver for disinformation – Peoples' disinformation behavior in health contexts
Abstract paper submitted to ASIS&T 24-Hour Global Conference
- Humboldt-Universität zu Berlin Germany
Disinformation, Health Information Behavior, Scientific Disinformation, Grounded Theory, Disinformation Behavior Model
Disinformation, Health Information Behavior, Scientific Disinformation, Grounded Theory, Disinformation Behavior Model
Agarwal, N. K., & Alsaeedi, F. (2021). Creation, dissemination and mitigation: toward a disinformation behavior framework and model. Aslib Journal of Information Management, 73(5), 639-658. https://doi.org/10.1108/AJIM-01-2021-0034
Baines, D. & Elliott, R. (2020). Defining misinformation, disinformation and malinformation: An urgent need for clarity during the COVID-19 infodemic. Department of Economics, University of Birmingham. Retrieved from (https://ideas.repec.org/p/bir/birmec/20-06.html).
Boutron, I., Haneef, R., Yavchitz, A., Baron, G., Novack, J., Oransky, I., ... & Ravaud, P. (2019). Three randomized controlled trials evaluating the impact of “spin” in health news stories reporting studies of pharmacologic treatments on patients'/caregivers' interpretation of treatment benefit. BMC medicine, 17(1), 105. https://doi.org/10.1186/s12916-019-1330-9 [OpenAIRE]
De Gani, S. M., Berger, F. M. P., Guggiari, E., & Jaks, R. (2022). Relation of corona-specific health literacy to use of and trust in information sources during the COVID-19 pandemic. BMC Public Health, 22(1), 42. https://doi.org/10.1186/s12889-021-12271-w
Fallis, D. (2015). What Is Disinformation? Library Trends, 63(3), 401-426. http://doi.org/10.1353/lib.2015.0014
Hahn, O., Lemke, S., Mazarakis, A., & Peters, I. (2020). Which visual elements make texts appear scientific? An empirical analysis. In Proceedings of the Conference on Mensch und Computer, September 2020, pp. 61- 65. https://doi.org/10.1145/3404983.3410014
Islam, M. S., Sarkar, T., Khan, S. H., Mostofa Kamal, A.-H., Hasan, S. M. M., Kabir, A. … & Seale, H. (2020). COVID-19-Related Infodemic and Its Impact on Public Health: A Global Social Media Analysis. The American Journal of Tropical Medicine and Hygiene, 103(4), 1621-1629. https://doi.org/10.4269/ajtmh.20-0812
Karlova, N. A., & Fisher, K. E. (2013). A Social Diffusion Model of Misinformation and Disinformation for Understanding Human Information Behaviour. Information Research, 18(1). Retrieved from (http://informationr.net/ir/18-1/paper573.html).
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!- Humboldt-Universität zu Berlin Germany
Abstract paper submitted to ASIS&T 24-Hour Global Conference