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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

 

Forthcoming talks

Achieving Consistent Low Latency for Wireless Real-Time Communications with the Shortest Control Loop

Thursday, 18 August 2022, 4.00pm to 5.00pm
Speaker: Zili Meng, Tsinghua Unversity
Venue: FW11 and https://cl-cam-ac-uk.zoom.us/j/97216272378?pwd=M2diTFhMTnppckJtNWhFVTBKK0REZz09

Real-time communication (RTC) applications like video conferencing or cloud gaming require consistent low latency to provide a seamless interactive experience. However, wireless networks including WiFi and cellular, albeit providing a satisfactory median latency, drastically degrade at the tail due to frequent and substantial wireless bandwidth fluctuations. We observe that the control loop for the sending rate of RTC applications is inflated when congestion happens at the wireless access point (AP), resulting in untimely rate adaption to wireless dynamics. Existing solutions, however, suffer from the inflated control loop and fail to quickly adapt to bandwidth fluctuations. In this paper, we propose Zhuge, a pure wireless AP based solution that reduces the control loop of RTC applications by separating congestion feedback from congested queues. We design a Fortune Teller to precisely estimate per-packet wireless latency upon its arrival at the wireless AP. To make Zhuge deployable at scale, we also design a Feedback Updater that translates the estimated latency to comprehensible feedback messages for various protocols and immediately delivers them back to senders for rate adaption. Trace-driven and real-world evaluation shows that Zhuge reduces the ratio of large tail latency and RTC performance degradation by 17% to 95%.

Speaker Bio: Zili is a 3rd-year PhD student in Tsinghua University. His current research interest focuses on real-time video communications. He has published several papers in SIGCOMM / NSDI and received the Microsoft Research Asia PhD Fellowship, Gold Medal of SIGCOMM 2018 Student Research Competition, and two best paper awards.

BSU Seminar: "Genome-wide genetic models for association, heritability analyses and prediction"

Monday, 22 August 2022, 4.30pm to 5.30pm
Speaker: David Balding, Honorary Professor of Statistical Genetics at UCL Genetics Institute and University of Melbourne
Venue: Seminar Rooms 1 & 2, School of Clinical Medicine, Hills Road, Cambridge CB2 0SP

Although simultaneous analysis of genome-wide SNPs has been popular for over a decade, the problems posed by more SNPs than study participants (more parameters than data points), and correlations among the SNPs, have not been adequately overcome so that almost all published genome-wide analyses are suboptimal. While there has been much attention paid to the shape of prior distributions for SNP effect sizes, we argue that this attention is misplaced. We focus on what we call the "heritability model": a low-dimensional model for the expected heritability at each SNP, which is key to both individual-data and summary-statistic analyses. The 1-df uniform heritability model has been implicitly adopted in a wide range of analyses. Replacing it with better heritability models, using predictors based on allele frequency, linkage disequilibrium and functional annotations, leads to substantial improvements in estimates of heritability and selection parameters over traits, and over genome regions, as well as improvements in gene-based association testing and prediction. Key collaborators Doug Speed, Aarhus, Denmark and Melbourne PhD student Anubhav Kaphle.

Statistics Clinic Summer 2022 III

Wednesday, 31 August 2022, 5.30pm to 7.00pm
Speaker: Speaker to be confirmed
Venue: Venue to be confirmed

If you would like to participate, please fill in the following "form":https://forms.gle/b1UzrTNBig7hkr1e7. The deadline for signing up for a session is 12pm on Monday the 29th of August. Subject to availability of members of the Statistics Clinic team, we will confirm your in-person or remote appointment.

This event is open only to members of the University of Cambridge (and affiliated institutes). Please be aware that we are unable to offer consultations outside clinic hours.

Statistics Clinic Summer 2022 IV

Wednesday, 21 September 2022, 5.30pm to 7.00pm
Speaker: Speaker to be confirmed
Venue: Venue to be confirmed

Abstract not available

Title to be confirmed

Monday, 26 September 2022, 3.00pm to 4.00pm
Speaker: Christopher Yau, University of Manchester
Venue: CRUK CI Lecture Theatre

Abstract not available