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Big Data Methods for Social Science and Policy - Interdisciplinary Workshop Programme

Thursday, 24 September 2015, 9.00am to 6.30pm
Location: Murray Edwards College, Cambridge

Big Data research is rapidly expanding in its contribution across the social sciences and in public policy. We now have the ability to draw on rich, varied and linked datasets as well as new forms of data on behaviour, mobility, and social processes via the internet, social media and sensor data, generated in large volumes and in real time. At the same time, innovations in data science, new computational technologies, and novel analytical methods have the potential to unlock the potential of these datasets.  Applying these theories and methods also raises ethical issues, making interdisciplinary collaboration essential for the application of big data to social science questions.

This interdisciplinary workshop brought together Cambridge research expertise in areas such as quantitative sociology, biostatistics, computing, mathematics, psychology, law and history and philosophy of science in order to explore what methodological insight can be offered from research advances in these disciplines.

The meeting featured a series of short talks, in-depth discussions and networking opportunities, allowing the opportunity to develop new connections and ideas for the application of big data to solve big questions in social science, as well as the societal, political and ethical implications of these new methods. 

Read the Big Data Workshop Summary at the Cambridge Public Policy SRI website.

 

Programme at a glance

Workshop Chair: Professor Anna Vignoles, Faculty of Education

Time

Session

Presentations

09:00-09:30

Registration and welcome

 

09:30-11:00

People and place –Location and geospatial data

Chair: Jon Crowcroft, Computer Laboratory

Cecilia Mascolo, Computer Laboratory - Mobile Sensing and Geo-Social data analysis for Social Science

Steve Marsh, Computer Laboratory - Real-world insights through geospatial analysis

Elisabete Silva, Department of Land Economy - Soft artificial intelligence, linking socio-economic and land spatial-led data analysis for urban planning

Mike Bithell, Department of Geography - Is social data big data? Challenges for global social models

Panel Discussion 

11:00-11:30

Break

 

11:30-13:00

Social media in social science and policy

Chair: Alex Kogan, Department of Psychology

David Stillwell, Psychometrics Centre - Predicting Psychology from Social Data

Joseph Chancellor, Department of Psychology - Combining data- and theory-driving insights using large, anonymous datasets of expressive online behavior

Rui Sun, Department of Psychology - Donations Predict Social Capital Gains for Low SES, But Not High SES Individuals and Countries

Kai Ruggeri, Department of Engineering - Using social media to inform global health policy: An example of major considerations regarding data for policy and policymakers

Panel Discussion 

13:00-14:00

Lunch

 

14:00-15:30

Government and census data – linkage, search and analysis

Chair: David Howarth, Faculty of Law

Andrew Means, The Impact Lab - The Role of Prediction in the Targeting of Services

Mihály Fazekas, Department of Sociology - Exploring government administrative data to hold governments accountable in the Big Data Era

Miguel Morin, Faculty of Economics - Adapting to Workplace Technological Change over the Long Run: Evidence from US Longitudinal Data

Tanvi Desai and Aidan Condron, ADRN – Facilitating access to Administrative and Big Data in the UK: the Administrative Data Research Network and the Big Data Network

Panel Discussion

15:30-16:00

Break

 

16:00-17:30

New tools and methods

Chair: John Naughton, CRASSH

Gabriel Recchia, CRASSH - The Unreasonable Effectiveness of Co-occurrence Based Models

Liang Wang, Computer Laboratory - Needle in a Haystack: Understanding the Tradeoff between Accuracy and Efficiency in Searching of High Dimensional Big Data

Nigel Collier, Department of Theoretical and Applied Linguistics - Natural Language Processing for Digital disease detection in a fast-moving world

Panel Discussion and closing remarks

17:30-18:30

Drinks and Networking