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Research
Impact
Exeter's Centre for Computational Social Science (C2S2) brings together international research-focused social scientists. C2S2 research takes an interdisciplinary and data-driven focus to address major societal challenges. Our approach to research is interdisciplinary and works across the 樱花动漫 and with a number of industry partners. C2S2’s interdisciplinary research activity also offers an opportunity for our students to learn-by-observing data analysis and to be part of cutting-edge research.
People
C2S2 at the 樱花动漫 has a total 17 core research staff across a number of disciplines including Politics, Sociology, International Relations and Criminology as well as over 20 affiliated staff and several industry partners. These staff have expertise in a number of areas including complex survey data, text analysis and network analysis. C2S2 has research funding from a variety of sources including the EU, ERSC and the Policing College Fund.
Themes
Exeter's Centre for Computational Social Science research focuses on the three themes of connecting people, society and data. These themes will provide scientifically coherent programmes of research aimed at driving forward innovations in social science theory, the development and application of novel research methods, and the collation and analysis of data sources.
The research programmes that sit within these research themes are:
This research programme looks at how social inequalities, and in particular inequalities in education, evolve and have an impact on individuals over the life course. To do this, we use high quality British longitudinal data sets, such as the National Pupil Database, Understanding Society, and the 1958 British Birth Cohort Study. Our projects include a study of how parental social class is associated with children鈥檚 educational attainment, a study of the effect of converting English schools to academies on educational trajectories of children with special educational needs, and a study of the role of education and lifestyle factors in fertility outcomes of UK couples.
Researchers: , , ,
Associate researchers: , , ,
Disciplines: Demography; Education; Social Science; Sociology
Topics: ageing; education; ethnic groups; fertility; inequalities; life-course; longitudinal studies.
Projects:
(Nitzan Peri-Rotem, the Understanding Society Biomarker Data Project Fellowship)
(Chris Playford, with Roxanne Connelly and Vernon Gayle, ESRC Secondary Data Analysis Initiative)
(Alexey Bessudnov, with Alison Black, Brahm Norwich and Yi Liu, ESRC Secondary Data Analysis Initiative)
(Alexey Bessudnov, with Brahm Norwich and George Koutsouris, Nuffield Foundation)
(Alexey Bessudnov, with Andrey Shcherbak, British Academy)
鈥孴he Policing Lab at C2S2 aims to promote evidence-based policing through research. We seek to understand and improve policing policy, practice and professionalism through innovative data use and the development of police data collection. The Policing Lab has successfully bid for ESRC IAA Strategic Initiative Fund to promote research collaborations with Devon & Cornwall Police. With more than 50 academics across the University and a large group of officers and staff in DCP, we are developing a network to facilitate co-production of rigorous research and promote evidence-based policing strategies.
Staff: Katharine Boyd, Brian Rappert
Disciplines: Interdisciplinary
Topics: criminology, policing, data collection/analysis
Funding has been available for co-produced projects between UoE and DCP. The overarching aim of the Policing Lab Fund is to further existing relations between Devon and Cornwall Police (DCP) and the 樱花动漫 through promoting evidence-based practice.
Policing Lab Fund 2019 Awardees -
Computational social science research at C2S2 looks at the intersection between computer science and social science. We have expertise in social networks, text as data and Bayesian inference.
Staff: Susan Banducci, Travis Coan, Lorien Jasny, Lamprini Rori, Oliver James, Alice Moseley, Gabriel Katz
Disciplines: Social Sciences and International Studies, Mathematics, Business
Topics: Computer Science, social networks, text as data
Projects: , Local Elections and Voter ID Pilots