Computational Social Science
Computational Social Science
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We are seeking an outstanding researcher with expertise in computational or mathematical psychology to join the Complex Human Data Hub and contribute to the school’s research and teaching program. The CHDH has areas of strength in memory, perception, categorization, decision-making, language, cultural evolution, and social network analysis. We welcome applicants from all areas of mathematical psychology, computational cognitive science, computational behavioural science and computational social science and are especially interested in applicants who can build upon or complement our existing strengths. We particularly encourage applicants whose theoretical approaches and methodologies connect with social network processes and/or culture and cognition, or whose work links individual psychological processes to broader societal processes. We especially encourage women and other minorities to apply.
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The CDT in NLP offers unique, tailored doctoral training comprising both taught courses and a doctoral dissertation over four years. Each student will take a set of courses designed to complement their existing expertise and give them an interdisciplinary perspective on NLP. The studentships are fully funded for the four years and come with a generous allowance for travel, equipment and research costs. The CDT brings together researchers in NLP, speech, linguistics, cognitive science and design informatics from across the University of Edinburgh. Students will be supervised by a world-class faculty comprising almost 60 supervisors and will benefit from cutting edge computing and experimental facilities, including a large GPU cluster and eye-tracking, speech, virtual reality and visualisation labs. The CDT involves a number of industrial partners, including Amazon, Facebook, Huawei, Microsoft, Naver, Toshiba, and the BBC. Links also exist with the Alan Turing Institute and the Bayes Centre.
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The Institute for Language, Cognition and Computation (ILCC) at the University of Edinburgh invites applications for three-year PhD studentships starting in September 2024. ILCC is dedicated to the pursuit of basic and applied research on computational approaches to language, communication and cognition. Primary research areas include: Natural language processing and computational linguistics, Machine Translation, Speech technology, Dialogue, multimodal interaction, language and vision, Computational Cognitive Science, including language and speech, decision-making, learning and generalization, Social Media and Computational Social Science, Human-Computer interaction, design informatics, assistive and educational technology, Information retrieval and visualization. Approximately 10 studentships from a variety of sources are available, covering both maintenance at the research council rate of GBP 19,162 (2024/25 rates) per year and tuition fees. Awards increase every year, typically with inflation. Studentships are available for UK, EU, and non-EU nationals.
Digital Traces of Human Behaviour: From Political Mobilisation to Conspiracy Narratives
Digital platforms generate unprecedented traces of human behaviour, offering new methodological approaches to understanding collective action, polarisation, and social dynamics. Through analysis of millions of digital traces across multiple studies, we demonstrate how online behaviours predict offline action: Brexit-related tribal discourse responds to real-world events, machine learning models achieve 80% accuracy in predicting real-world protest attendance from digital signals, and social validation through "likes" emerges as a key driver of mobilization. Extending this approach to conspiracy narratives reveals how digital traces illuminate psychological mechanisms of belief and community formation. Longitudinal analysis of YouTube conspiracy content demonstrates how narratives systematically address existential, epistemic, and social needs, while examination of alt-tech platforms shows how emotions of anger, contempt, and disgust correlate with violence-legitimating discourse, with significant differences between narratives associated with offline violence versus peaceful communities. This work establishes digital traces as both methodological innovation and theoretical lens, demonstrating that computational social science can illuminate fundamental questions about polarisation, mobilisation, and collective behaviour across contexts from electoral politics to conspiracy communities.