项目介绍

2021年8月4日

About the course

The multidisciplinary DPhil in Social Data Science provides opportunity for highly qualified students to undertake cutting- edge research focused on using unstructured heterogeneous data about human behaviour in a theoretically informed manner, thereby advancing our understanding of social processes.

Social traces – often generated digitally from, for example, social media, communications platforms, devices, sensors/wearables, and mobile phones – offer a way to accumulate new large-scale data, in addition to existing archives and repositories that have been converted to digital formats. Such data can be put to work helping us understand old and new foundational problems of crucial interest to the social sciences, industry, and policy-makers including social, economic and political behaviour, interpersonal relationships, market design, group formation, identity, international movement, ethics and responsible ways to enhance the social value of data, and many other topics.

The growing field of social data science involves developing the science of these social data: creating viable datasets out of messy, real world data; and developing the tools and techniques to analyse them to tell us something about the world, through explanation, prediction and the testing of interventions. In this way, social data science offers a data science where the data relates to individual and social behaviour and a theoretically informed social science with generation and analysis of real-time transactional data at its centre.

Over the course of the three to four years, you are expected to produce an important and original piece of scholarship that will make a significant contribution to the dynamic area of Social Data Science. On completion, you will have the qualities and transferable skills necessary to excel in teaching, research, policymaking or business.

The DPhil programme at the Oxford Internet Institute (OII) is also available on a part-time basis. The part-time programme is spread over six to eight years of study and research. The part-time degree offers the flexibility of part-time study with the same high standards and requirements as the full-time DPhil programme. The part-time DPhil also provides an excellent opportunity for professionals in high tech industries to undertake rigorous long-term research that may be relevant to their working life. Please visit the department website for further details on part-time doctoral study or contact the Graduate Studies Assistant.

Supervision

The allocation of graduate supervision for this course is the responsibility of the Oxford Internet Institute and it is not always possible to accommodate the preferences of incoming graduate students to work with a particular member of staff.

Supervision for the DPhil in Social Data Science spans multiple departments (please see the full list of faculty members eligible to supervise DPhil students for this programme). A supervisor may be found outside the list on the course web page, and co-supervision is also possible.

Assessment

All students will be initially admitted to the status of Probationer Research Student (PRS). Within a maximum of six terms as a full-time PRS student or eight terms as a part-time PRS student, you will be expected to apply for transfer of status from Probationer Research Student to DPhil status. This application is normally made by the fourth term for full-time students and by the sixth term for part-time students.

A successful transfer of status from PRS to DPhil status will require satisfactory completion of such lectures, seminars and classes (with a mark of 50 or higher) as the Graduate Studies Committee of the OII shall determine. Following successful transfer, students will need to apply for and gain confirmation of DPhil status to show that the work continues to be on track. This will need to be completed within nine terms of admission for full-time students and twelve terms of admission for part-time students.

Both milestones involve an interview with two assessors (other than your supervisor).

Full-time students will be expected to submit an original thesis of not more than 100,000 words three or, at most, four years from the date of admission. If you are studying part-time, you be required to submit your thesis after six or, at most, eight years from the date of admission. To be successfully awarded a DPhil in Social Data Science you will need to defend your thesis orally (viva voce) in front of two appointed examiners.

Graduate destinations

Employers recognise the value of a degree from the University of Oxford, and graduates from our existing programmes have secured excellent positions in industry, government and NGOs. Alumni who have pursued academic careers have taken up research and teaching positions at the University of Oxford, Cornell University, University of Hong Kong, Imperial College London, Durham University, University of New South Wales, Coventry University, University of Leicester, University of Ottawa and Michigan State University. OII DPhil alumni also work in wide-range of organisations including The World Bank, Oxfam, Cisco, McKinsey and Google.

The OII Alumni Wall features interviews from both MSc and DPhil alumni about their time at the Department and career paths after Oxford.

Changes to this course and your supervision

The University will seek to deliver this course in accordance with the description set out in this course page. However, there may be situations in which it is desirable or necessary for the University to make changes in course provision, either before or after registration. The safety of students, staff and visitors is paramount and major changes to delivery or services may have to be made in circumstances of a pandemic (including Covid-19), epidemic or local health emergency. In addition, in certain circumstances, for example due to visa difficulties or because the health needs of students cannot be met, it may be necessary to make adjustments to course requirements for international study.

Where possible your academic supervisor will not change for the duration of your course. However, it may be necessary to assign a new academic supervisor during the course of study or before registration for reasons which might include illness, sabbatical leave, parental leave or change in employment.

For further information please see our page on changes to courses and the provisions of the student contract regarding changes to courses.

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