I received my PhD in Computer Science from the University of Southampton, UK. I was in the Web and Internet Science group, supervised by Prof Luc Moreau and Prof Susan Halford. My PhD focused on causal inference for estimating the social influence of online communications on real-world outcomes, at the individual and at the collective level. My PhD research was honoured with the Best Poster award for the poster accompanying my full-length paper (in proceedings) at the 2016 International Conference on Social Informatics in Seattle, Washington.
I hold a PhD in Computer Science from the University of Southampton (2018), an MSc in Operational Research from the University of Southampton (2014, Distinction, dissertation prize, full scholarship), and a BA (Hons) in Computer Science from the University of Cambridge (2012, 2.1, dissertation high commendation).
My research focus is on 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 on SpringerLink, poster as pdf] Best Poster Award for the accompanying poster, 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 (cover story above the fold and further articles), The New York Times (cover story 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) [more details]
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, September). Projecting Dental Care Need in England over the Next 20-30 Years. Masters Thesis. Sponsor Award.
Liotsiou D. (2012, June). 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).
During my PhD, I demonstrated and/or marked for the following courses and short seminars:
- Java programming labs, undergraduate-level (demonstator)
- Funtional programming in Scheme, undergraduate-level (marker)
- Social network analysis, postgraduate-level (group project mentor)
- Software engineering, undergraduate-level (group project mentor)
- Introduction to Data Science in Python, for secondary-education teachers
- Introduction to Machine Learning in Python, for PhD students
Dimitra (Mimie) Liotsiou,
Oxford Internet Institute,
University of Oxford,
1 St Giles,
Oxford, OX1 3JS,