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Connection between digital literacy and susceptibility to misinformation

   Faculty of Management, Law and Social Sciences

  Dr Elvira Ismagilova, Dr Kuttimani Tamilmani,  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Social media is a source of various types of misinformation (Su, 2021; Shin et al., 2018). Decisions to share content on social media can be made in seconds. It is argued that misinformation can spread more broadly in comparison with accurate information and sometimes posts containing misinformation can become more popular than accurate posts (Islam et al., 2020; Lanius et al., 2021). Misinformation can have serious consequences for society, businesses, and public authorities (e.g., panic buying, manipulation of the outcomes of elections, spread of infection, shortage of essentials, mental health problems etc.) (Naeem & Ozuem, 2021). Prior research has shown some individuals are more likely to believe misinformation than the others depending upon the individual characteristics (e.g., Age, Education etc)

This project aims to explore the relationships between digital literacy and vulnerability to misinformation on social media platforms. 

The potential candidate will need to demonstrate familiarity with existing research literature on misinformation and digital literacy. The candidate should be inclined towards advanced quantitative research approach to gather and analyse data. Knowledge of statistical techniques such as linear and non-linear regression, and structural equation modelling could prove to be an additional advantage.

The supervisory team welcomes informal inquiries from potential candidates to discuss the research project; formal applications should be made via the University of Bradford web site.

Funding Notes

This is a self-funded PhD project; applicants will be expected to pay their own fees or have a suitable source of third-party funding. UK students may be able to apply for a Doctoral Loan from Student Finance for financial support.


Islam, A. N., Laato, S., Talukder, S., & Sutinen, E. (2020). Misinformation sharing and social media fatigue during COVID-19: An affordance and cognitive load perspective. Technological Forecasting and Social Change, 159, 120201.
Lanius, C., Weber, R., & MacKenzie, W. I. (2021). Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey. Social Network Analysis and Mining, 11(1), 1-15.
Naeem, M., & Ozuem, W. (2021). Understanding misinformation and rumors that generated panic buying as a social practice during COVID-19 pandemic: evidence from Twitter, YouTube and focus group interviews. Information Technology & People.
Shin, J., Jian, L., Driscoll, K., & Bar, F. (2018). The diffusion of misinformation on social media: Temporal pattern, message, and source. Computers in Human Behavior, 83, 278-287.
Su, Y. (2021). It doesn’t take a village to fall for misinformation: Social media use, discussion heterogeneity preference, worry of the virus, faith in scientists, and COVID-19-related misinformation beliefs. Telematics and Informatics, 58, 101547.

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