Graduate Programs in Social Data Science to Commence at Oxford and the London School of Economics
Career Insightsposted by Alex Amari July 10, 2018 Alex Amari
This fall, new interdisciplinary master’s programs integrating social sciences and data science will commence at two of the UK’s top universities. Oxford University’s Oxford Internet Institute, a multi-disciplinary center for the study of social and computer sciences, will offer a 1-year MSc in Social Data Science to approximately 25 students, followed by a PhD program in the subject beginning in fall 2019. At the same time, the London School of Economics’ Department of Methodology will offer a 1-year MSc in Applied Social Data Science. The new programs will be among the first in the world to focus explicitly on the overlap between social and behavioral sciences and the glowing-hot fields of data science and artificial intelligence.
The two master’s programs follow the convening of social data science centers and working groups at some of Europe’s most impactful data science institutions. For example, the London-based Alan Turing Institute, the UK’s national institute for data science and artificial intelligence, is home to a working group in social data science with researchers from the Universities of Cambridge, Oxford, Warwick, and Edinburgh.
According to its site, the group is working on, “developing foundational theories of human behaviour at diverse social and temporal scales” as well as “identifying methodological challenges and solutions to enable social data science to deliver robust and credible results in key application domains,” with the support of high-profile partners such as Google, Twitter, and Facebook.
An entryway at The Alan Turing Institute in London, which convenes a social data science working group. (Image source: turing.ac.uk)
The Oxford and LSE programs, like the institutional working groups, will seek to address two major exigencies in data science. Both major needs stem from the ever-growing amount of ‘social data’ generated by social media, communications platforms, Internet of Things [IoT] devices, sensors/wearables, and mobile phones, among other sources.
First, the programs will seek to prepare more students to tackle questions of import to the social sciences using new techniques in big data and AI.
“We’ve entered a phase where we suddenly have the potential to measure behavior at a global scale, much more rapidly than we could before, at much lower cost than we could before, and, potentially, have the opportunity to measure behaviors that we couldn’t capture before now” says Dr. Suzy Moat, a researcher at the University of Warwick and member of the working group at the Alan Turing Institute.
But some experts have lamented an apparent lack of social science students with the computational and quantitative skills necessary to generate insights using social data, particularly in the UK. “We now have access to a lot of large datasets collected either at a British or a European level, but we lack people with the skills to make use of it,” says Brendan Burchell, director of the Cambridge Undergraduate Quantitative Methods Centre, housed within the University’s Department of Sociology. “It’s been a bigger problem in the UK than in other countries because a lot of our school kids specialise and give up doing maths at a younger age, and there’s this idea that if you were good at numbers you’d end up doing physics or natural sciences and if you weren’t good at numbers you’d end up doing social science.”
In addition to preparing new social data scientists to work with the ever-increasing troves of social data, the new master’s programs will also emphasize some of the ethical challenges of working with data on human beings.
In as much as the methodological challenges of social data are technical, as in cases of working with unstructured social datasets, they’re also moral in nature. Working consistently with data via new technologies raises questions surrounding peoples’ rights to their own data, rights to privacy, and the rules that should face researchers, for-profit companies, and government institutions in using those data.
Such issues have been hot topics in the global data science community – all the more so in the wake of data breaches like the Facebook Cambridge Analytica Scandal, in which a British data mining firm used data on roughly 50 million unaware Facebook users to support political clients like the 2016 Trump Presidential campaign and the ‘Leave’ campaign in Britain’s Brexit referendum. At the same time, legislators are testing new policies aimed at curtailing private industry’s increasing access and use of people’s personal data. Chief among these has been the momentous enactment of the European Union’s GDPR last month.
In light of the rapidly changing public landscape, these new social data science programs at Oxford and LSE seem poised to contribute to unfolding debates about data science ethics and to produce data scientists capable of adding to the discussion in graduate destinations including government and industry roles.