项目介绍

2021年8月4日

About the course

The combined multidisciplinary MSc + DPhil in Social Data Science provides the social and technical expertise needed to analyse unstructured heterogeneous data about human behaviour, thereby informing understanding of the human world. 

Social data generated digitally (from, for example, social media, communications platforms, Internet of Things (IoT) devices, sensors/wearables, and mobile phones) offer a way to accumulate new large-scale data, in addition to existing data that have been converted to digital formats. These data can be put to work helping us understand big issues 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 social science with generation and analysis of real-time transactional data at its centre.

Please note that the MSc component is also offered separately as the MSc in Social Data Science.  

It is possible to study the DPhil component of the combined programme on either a full-time or part-time basis. Over the course of the full-time DPhil component 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 part-time version of the DPhil component has the same high standards and requirements as the full-time version, but is spread over 6-8 years. Please visit the department website for further details on part-time doctoral study or contact the department using the details provided under Further information and enquiries. 

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 MSc in Social Data Science spans multiple departments (a full list of faculty members eligible to supervise students for this programme can be found on the department’s website – see Further information and enquiries). A supervisor may be found outside the list on the course webpage, and co-supervision is also possible. 

Assessment

During your full-time MSc year, you will take a combination of core and option papers and produce a thesis of up to 15,000 words with the support of a thesis supervisor. The thesis provides you the opportunity to apply the methods and approaches you have covered in the other parts of the course and carry out a substantive piece of academic research.

Students admitted directly to the MSc + DPhil in Social Data Science will still need to meet the normal admissions requirements and any conditions set to progress to the DPhil in Social Data Science.

During the DPhil element of the course, 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, 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.

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.

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

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. 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, NGOs, or have gone on to pursue doctoral studies at top universities.

For example, non-academic destinations of recent graduates have included large Internet companies such as Google or Facebook, smaller start-ups like Academia.edu, as well as regulatory positions and consultancies. OII DPhil 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 among others.

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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