ODISSEI welcomes proposals for presentations on Computational Social Science to be given at its conference on 3 November 2022 in Utrecht. ODISSEI, the research infrastructure for social science in the Netherlands, connects researchers with the necessary data, expertise and resources to conduct ground-breaking research and embrace the computational turn in social enquiry. This conference seeks to bring together a community of computational social scientists to discuss data, methods, infrastructure, ethics and theoretical work related to digital and computational approaches in social science research.
Topics explicitly encouraged (but are not limited to):
- Theoretical discussions and concepts in Computational Social Science;
- Social science research utilising ODISSEI Infrastructure (such as CBS Microdata, LISS panel, or OSSC);
- Computational methods for social science research (such as agent based modelling, network analysis, textual analysis, benchmarking, and machine learning);
- Causal Inference in Computational Social Science;
- Ethical and legal issues of algorithms, big data and computational methods;
- The use of computational methods to inform policy;
- Bias, inclusivity, and inequalities in Computational Social Science;
- Use of High Performance Computing for Social Science Research;
- The use of new technologies in Social Science Research;
- Computational Social Science Research with links to the humanities or health sciences;
- The development and building of social science research infrastructure.
Presentations at the conference last 15 mins, in addition there will be a poster session. There will be no pre-circulated papers. Presentations can be of published work, in preparation for publication or work in-progress. Submissions are open to researchers from all career stages, including PhD Candidates and Master students. Abstracts of up to 300 words should be submitted via EasyChair no later than 30 June 2022 (CEST).
Professor Frauke Kreuter, Co-director of the Social Data Science Center and faculty member in the Joint Program in Survey Methodology (JPSM) at the University of Maryland, USA; Professor of Statistics and Data Science at the Ludwig-Maximilians-University of Munich, Germany and head of the statistical methods group at the Institute for Employment Research (IAB) in Nuremberg, Germany. She is co-editor of Big Data and Social Science. Data Science Methods and Tools for Research and Practice (CRC Press, Second Edition 2021).
Professor Matthew Salganik, Professor of Sociology at Princeton University, and Director of the Center for Information Technology Policy. He is also affiliated with several of Princeton’s interdisciplinary research centers including the Office of Population Research and the Center for Statistics and Machine Learning. His research interests include social networks and computational social science. He is the author of Bit by Bit: Social Research in the Digital Age (Princeton University Press, 2019).
Conference registration: Free
Conference date: 3 November 2022
Location: Utrecht, the Netherlands
Deadline for abstracts: 30 June 2022 (CEST)