June 22-23 2017, Centre for Reasoning, University of Kent, Canterbury, UK
Jonathan Bright (University of Oxford)
Jörg Müller (Universitat Oberta de Catalunya)
Chidiebere Ogbonnaya (University of East Anglia)
Wolfgang Pietsch (Technical University of Munich)
Federica Russo (Universiteit van Amsterdam)
Over the past few years, big data has been the focus of considerable research effort. One of the main motivations is the potential for using big data to learn causal relationships. In particular, significant challenges and opportunities arise from big data resulting from human interactions that are recorded via web, sensors and mobile device, or revealed through digitization of historical records. Society faces a transformative data deluge, from which knowledge can be extracted.
However, one can question how big data should be employed in the study of social phenomena, and what the methodological implications are of using it to obtain causal knowledge. What conceptual framework is required to establish causal inferences from big data? Can big data offer evidence of social mechanisms? Which algorithms are appropriate for the analysis of a particular social outcome?
This conference seeks to explore methodological implications of using big data for causal discovery in the social sciences. The conference will bring together philosophers and social scientists.
14.00-15.00 Wolfgang Pietsch “Causation, probability and all that: Data science as a novel kind of inductive methodology”
15.00-16.00 Chidiebere Ogbonnaya “Employment practices, employee well-being and organizational performance: A 2-1-2 multilevel mediation analysis”
16.15-17.15 Federica Russo and Jean-Christophe Plantin “Big data and the question of objectivity”
9.15-10.15 Robert Northcott “How big data has – and hasn’t – helped prediction in social science”
10.15-11.15 Jörg Müller “Doing and undoing social ties. Thinking about ‘distributed action’ using sensor-based data”
11.30-12.30 Stefano Canali “Methodological Novelties and Causal Inference in Epidemiology”
13.30-14.30 Martina Patone “A framework for assessing selection bias in Twitter data”
14.45-15.45 Jonathan Bright “Studying online politics with big data: beyond the sample paradigm”
Registration is free but compulsory. There are a limited number of places so please register early. Please register via email to email@example.com.
This conference is organised by Virginia Ghiara on behalf of the Centre for Reasoning at the University of Kent and the Eastern ARC Consortium.
For any queries please contact Virginia Ghiara: firstname.lastname@example.org