The Place for Learning and Analysing Complex Environmental Lab
The Place Lab (PLACE) works with research and non-governmental organisations to understand democracy in the digital age combining advanced computational and quantitative approaches with social science insights.
The PLACE Lab is a research centre at the University of Strathclyde dedicated to understanding government transparency, political communications, and algorithmic governance through advanced quantitative methods including machine learning and artificial intelligence.
Our distinctive approach applies rigorous social science methodologies to examine how AI and computational systems shape democratic processes, public policy, and political behaviour.
Research Focus
- Government Transparency - examining openness and accountability in public institutions
- Political Communications - analysing how political messages spread in digital environments
- AI Bias Assessment - evaluating algorithmic systems from a social science perspective
- Computational Methods - developing quantitative approaches to complex political questions.
Research Themes
Algorithmic Bias and Fairness
Our flagship program examines biases in AI algorithms from a social science perspective:
- How algorithmic systems reproduce social inequalities
- Political and ethical implications of automated governance
- Methods for detecting bias in machine learning
- Impact on marginalized communities and democratic representation
Government Transparency and Accountability
- Freedom of information and open data initiatives
- Transparency in algorithmic governance
- Public sector AI use and democratic oversight
- Effectiveness of accountability mechanisms
Political Communications in Digital Environments
- Social media and political polarization
- Misinformation and disinformation
- Political advertising and micro-targeting
- Computational propaganda
Computational Methods for Social Science
- Machine learning applications in political research
- Natural language processing for political texts
- Network analysis
- Causal inference methods
Who's Involved
The PLACE Lab consists of a team of scholars from across the Humanities and Social Sciences using computational social science approaches such as machine learning, network analysis and artificial intelligence for studying political communications.
Zoe Greene, PhD
Director
Professor in Political and Computational Social Science
Research in Political communications, Party Politics, computational methods, AI governance
Chamil Rathnayake, PhD
Senior Lecturer in Journalism, Media and Communications
Research Interests in Social Media, Disinformation, Network Analysis, AI Governance
_(1).png "Timea Balogh")
Timea Balogh
Politics
Lorenzo Crippa
Politics
Elise Frelin
Politics
Narisong Huhe
Politics
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Louise Luxton
Politics
Camila Mont'Alverne
Journalism, Media & Communications
Dayei Oh
Journalism, Media and Communications
Tom Scotto
Politics
_(1).jpg "Christine Sylvester")
Christine Sylvester
Politics
_(1).jpg "Giulia Venturini")
Giulia Venturini
Politics
Elaine Webster
Law
Projects
Current Projects
- Assessing Algorithmic Bias in Public Services - examining AI decision-making across UK public services, evaluating technical fairness measures alongside political, ethical, and social implications.
- Government Transparency in the Digital Age - investigating whether traditional accountability mechanisms remain effective in an era of algorithmic governance. See ParliView.org for additional information.
- Political Misinformation Networks - using network analysis and machine learning to understand how false political information spreads.
Get Involved
Join us
We welcome inquiries from prospective PhD students, postdoctoral researchers, and visiting scholars.
Contact us
The PLACE Lab
Department of Politics
Department of Government & Public Policy
University of Strathclyde
Lord Hope Building
141 St James Road
Glasgow, G4 0LT
Email: TBD
BlueSky: @strathplacelab.bsky.social