At the Oxford Internet Institute, I am working on the analysis of computational propaganda on social media. My PhD work focuses on social influence and causality on the Web - particularly, on estimating social influence of Web-mediated communications on real-world outcomes, at the collective and at the individual level. More broadly, I am interested in developing computational models and methods for understanding and analysing patterns of behaviour in online interactions, informed by the social sciences. My research interests relate to the areas of online social influence, causal inference, social network analysis, computational social science, and data science.
Liotsiou, D., Moreau, L., & Halford, S. (2016, November). Social Influence: From Contagion to a Richer Causal Understanding. In International Conference on Social Informatics (pp. 116-132). Springer International Publishing. [paper, poster] Best Poster Award for poster accompanying 17-page full length paper in proceedings.
Howard, P. N., Ganesh, B., Liotsiou, D., Kelly, J., & François, C. The IRA, Social Media and Political Polarization in the United States, 2012-2018. (2018). Working Paper 2018.2. Oxford, UK: Project on Computational Propaganda.comprop.oii.ox.ac.uk. 46 pp. (Author order: Oxford P.I., then Oxford postdocs alphabetically, then collaborators from Graphika).
Selected press coverage: The Washington Post (front page above the fold, and further articles), The New York Times (front page above the fold, and further articles), PBS News Hour, ABC News, BBC, The Guardian, The Independent, Ars Technica (with interview quotes), Yahoo Finance (with interview quotes) [links and more press coverage].
Liotsiou, D., Kollanyi, B., and Howard, P. N. (2019). The Junk News Aggregator: Examining junk news posted on Facebook, starting with the 2018 US Midterm Elections. arXiv preprint arXiv:1901.07920.
Press coverage: TechCrunch, Newsweek, the Bulletin of the Atomic Scientists (video interview).
Liotsiou, D., Moreau, L., & Halford, S. (2017, work in progress). A Causal Methodological Framework for Conceptualising and Measuring Social Influence in Online Communications Using Observational Data.
Liotsiou, D., Moreau, L., & Halford, S. Key Limitations of the Contagion Paradigm for Online Social Influence, and how to Address them.
Liotsiou, D., Kollanyi, B. & Howard, P. The Junk News Aggregator: Analysing Engagement with Junk News on Facebook in the Context of the 2018 US Midterm Elections.
Liotsiou, D., Kollanyi, B. & Howard, P. Comparing social media Engagement across Traditional News, Online News, and Junk News, in the Context of the 2018 US Midterm Elections.
Liotsiou, D., Chaslot, G. & Howard, P. Algorithmic Transparency on YouTube: Assessing Bias in YouTube’s Algorithmic Video Recommendations through Network Analysis.
Liotsiou D. (2018, October). Measuring the Social Influence of Online Communications at the Individual and Collective Level: A Causal Framework. PhD Thesis. [abstract]
Liotsiou D. (2014, June). Projecting Dental Care Need in England over the Next 20-30 Years. Masters Thesis. Sponsor Award.
Liotsiou D. (2012, September). Parallelising Ant Colony Optimisation-based Solutions to the Vehicle Routing Problem in Scala. Undergraduate Thesis. High Commendation.
- Social Influence: from Contagion to a Richer Causal Understanding. The 5th annual UK Causal Inference Meeting (2017), University of Essex, United Kingdom.
- Social Influence: from Contagion to a Richer Causal Understanding. Data Natives Meeting (2017), City, University of London, United Kingdom.
Reviewer for EPJ Data Science (2018).