Fake news and social media
There is much to do about the dissemination of fake news through social media. According to the news media, for instance, fake news might have played a role in election of the US president in 2016 – Trump versus Clinton, as fake news messages were more often retweeted than authentic news. The dissemination of fake news has thus been identified as an important challenge to modern society. This leads to the overarching question how its impact can be reduced.
Within the theme of fake news and disinformation, a number of relevant research questions can be distinguished. Examples are:
1. How do people assess whether a news items is genuine or fake, and what are the crucial characteristic(s) of a news item that determine a news item’s perceived credibility?
2. Which individual characteristics determine to what extent people are alert to the possibility of a news item being distorted or fake? To what extent is deception awareness related to variables as the heuristic and systematic information processing styles?
3. There are initiatives to design interventions aimed at influencing the deception awareness among people. What is the effect of a particular intervention in creating awareness of news items potentially being fake or distorted?
4. Some people put a lot of effort into correcting fake news items (e.g. on Twitter). What is the impact of such corrections on the perceived credibility of the news item, the reputation of the author of the news item and the attitudes on the topic of the users of the social medium? Does the tone-of-voice in these correction tweets affect the responses of the users?
The topic of the research questions will be specified in consultation with the student. The topic should relate to a research theme within the Department of Psychology of Conflict, Risk and Safety, preferably one that focuses on risk perception and communication.
The research method depends on the question. The most obvious ones are interviews, survey and experiment.
The data of quantitative studies will be analysed by data analysis programmes such as SPSS or R. For qualitative studies, Atlas.ti might be used
There is already a broad range of literature on fake news. A good place to start might be:
David M. J. Lazer et al. (2018). The science of fake news. Science, Vol. 359, Issue 6380, pp. 1094-1096. DOI: 10.1126/science.aao2998. http://science.sciencemag.org/content/359/6380/1094
Are you interested in this topic for your thesis? Please contact the BA-Thesis coordinator, Jan Gutteling (firstname.lastname@example.org)