An Introduction to Computer Vision for Social Scientists

This one-day workshop introduces social scientists to the systematic analysis of images and videos as data. Visual material is central to politics, communication, and culture, yet many researchers are unfamiliar with the computational tools that allow its study at scale. The workshop offers an accessible entry point to computer vision, highlighting both core methods and their applications in the social sciences.

The morning session provides a conceptual overview of computer vision. Participants will be introduced to the basics of deep learning and convolutional neural networks, the foundation of most modern methods. We will review approaches such as image classification, object and face detection, and multimodal techniques that combine text and images. Examples of research using computer vision in social science contexts will be discussed, alongside key ethical considerations, best practices, and infrastructural requirements for large-scale visual data analysis.

The afternoon session is hands-on, focusing on image classification in Python with PyTorch on Google Colab. Participants will build a machine learning pipeline using an open-source dataset, covering data preparation, model design, training, and evaluation with standard metrics. By the end, attendees will have trained and tested their own classifier and gained a practical foundation for applying computer vision in research. Please note that participants will need some previous programming experience with Python.

Outcomes:

By the end of this training session, participants will be able to:

• Explain how images and videos can be systematically used as data in social science research;
• Understand the basic principles behind key computer vision techniques, including image classification and object/face detection;
• Gain hands-on experience running beginner-friendly Python code to implement simple computer vision tasks;
• Critically assess the opportunities and limitations of applying computer vision methods in different areas of social science;
• Identify potential applications of computer vision for their own research projects and future studies.

Contributors:

Dr Andreu Casas is Associate Professor in Political Communication at Royal Holloway, University of London, and director of the London Social Media Observatory. His research focuses on how digital media shapes policy, collective action, polarisation, and legislative dynamics through innovative computational approaches to text and image data.

Dr Asra Aslam is a Lecturer in Data Science at the University of Sheffield, specialising in AI, machine learning, computer vision, and their applications in health sciences. She has led projects on AI-driven healthcare, collaborated with industry and public bodies such as Transport for London, and received multiple national and international awards recognising her contributions to AI, health, and EDI.

Dr Dani Madrid-Morales is a Lecturer in Journalism and Global Communication at the University of Sheffield, and Deputy Director of the WRDTP’s Digital Technologies, Communication and Artificial Intelligence (DCA) Pathway. His research is centred around the study of global political communication and international media flows, with a focus on the Global South.

Important:

• This is an in-person event at the University of Sheffield (lunch and refreshments will be provided).
• This event is open to members of WRDTP partner institutions and other ESRC DTPs.
• Bookings will close at 9.00am on Wednesday 8th April.
• When booking, we ask that you use your institutional (.ac.uk) email address and complete all fields of the booking form. Thank you for your understanding.

Please note: The WRDTP is committed to sustainability and to reducing the waste from excess catering at events. A key challenge here is non-attendance at events. From October 1st 2025, the WRDTP will be changing the way we manage the non-attendance of PGR students who have booked place/s at WRDTP Training events. Any PGR student who does not inform the WRDTP (via [email protected]) that they will not be able to attend a WRDTP event at least 3 working days before the event takes place will have the cost of their place deducted from their RTSG (if a WRDTP-funded student), or have this charged to their department (if not funded by the WRDTP). This will allow us to better plan for events and to avoid catering waste. Thank you in advance for your cooperation on this matter.

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Host or Publisher White Rose DTP