I am Reader (Associate Professor) in Computational Social Science at the University of Edinburgh School of Informatics. In my research, I develop and use computational methods from natural language processing and artificial intelligence, social network analysis and agent-based modelling to study social media and related technologies. A key focus of my research is to explore different aspects of social media, such as misinformation, hate speech, and the malicious use of automation (bots). I also examine issues with these methods including data collection practices, fairness, bias and AI ethics.
At Edinburgh, I am the Deputy Director of the Institute for Language, Cognition and Computation, Co-Director of the SMASH group, and part of the management team of the CDT in NLP. I also help run the Social Data Science Hub. Before working here, I was a postdoctoral researcher at the University of Duisburg-Essen, where I also completed my PhD. I am an Associate Editor of Business & Information Systems Engineering, in the Senior Programme Committee of ICWSM, and was Ethics Co-Chair of ACL 2025.
PhD, 2019
University of Duisburg-Essen
MSc in Computer Science, 2016
University of Münster
Exchange year, 2014-5
University of Strasbourg
BSc in Information Systems, 2013
University of Münster
Chausson, Sandrine; Fourcade, Marion; Harding, David J; Ross, Björn; Grégory Renard (2025). The Insight-Inference Loop: Efficient Text Classification via Natural Language Inference and Threshold-Tuning. Sociological Methods & Research. [doi]
Calabrese, Agostina; Neves, Leonardo; Shah, Neil; Bos, Maarten W.; Ross, Björn; Lapata, Mirella; Barbieri, Francesco (2024). Explainability and Hate Speech: Structured Explanations Make Social Media Moderators Faster. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), Bangkok, Thailand, August 2024, pp. 398–408. [doi]
Ungless, Eddie L; Ross, Björn; Belle, Vaishak (2023). Potential Pitfalls With Automatic Sentiment Analysis: The Example of Queerphobic Bias. Social Science Computer Review 41 (6), pp. 2211–2229. [doi]
Winter, Stephan; Neubaum, German; Stieglitz, Stefan; Ross, Björn (2021). #OpinionLeaders: A comparison of self-reported and observable influence of Twitter users. Information, Communication & Society (ICS) 24(11), pp. 1533–1550.
Jung, Anna-Katharina; Ross, Björn; Stieglitz, Stefan (2020). Caution: Rumors ahead – The debunking of false information on social media. Big Data & Society 7(2).
Ross, Björn; Pilz, Laura; Cabrera, Benjamin; Brachten, Florian; Neubaum, German; Stieglitz, Stefan (2019). Are social bots a real threat? An agent-based model of the spiral of silence to analyse the impact of manipulative actors in social networks. European Journal of Information Systems (EJIS), 28(4), pp. 394–412.
For information on pursuing a PhD at the University of Edinburgh, please feel free to contact me directly by email and send some information about your research interests and your CV.
PhD funding in Informatics is typically allocated in fixed cycles: the application deadline for starting your PhD in September of any given year tends to be sometime between November and January (i.e., 8-10 months before the PhD starts) for international students, a bit later for “home fees” students. Around October-November is a good time to be contacting potential supervisors.
I am open to supervising self-proposed dissertation projects. If you are currently an Edinburgh student on one of our programmes and you would like to self-propose a project, please get in touch with me a few weeks before the deadline.
In the academic year 2025-26, I am Course Organiser for Evidence, Argument and Persuasion in a Digital Age at the Edinburgh Futures Institute, and I deliver lectures on Text Technologies for Data Science at the University of Edinburgh School of Informatics and on the cross-College course Understanding Society with Big Data: Computational Social Science.