AI for Understanding and Safeguarding Online Social Networks: Mapping Dynamics and Countering Threats

About the Project

Online social networks have become central to how people share news, form opinions, and connect with communities, shaping both social behaviour and public perception on a global scale. These networks enable rapid communication and open discourse, allowing diverse voices to be heard across cultural and geographic boundaries. However, online social networks are also vulnerable to the spread of disinformation, coordinated manipulation, and algorithmic echo chambers that can distort reality, polarise groups, increase disagreement, and deepen inequalities. Studying online social networks provides vital insights into the forces that shape online interactions, both positive and harmful, and supports the development of strategies to safeguard networks and reduce negative effects while promoting open dialogue, freedom of expression, and fair access to information. This project will use artificial intelligence (AI) techniques to analyse online social networks and their impacts on users, communities, and society. The knowledge gained can be applied to real-world problems such as detecting and countering disinformation, improving content recommendation, enhancing online engagement, and supporting evidence-based policy or platform design. It will also foster expertise in assessing the broader impact of social networks on society, communities, youth, and children, enabling organisations, educators, and policymakers to create safer and more positive online environments. These skills are valuable across sectors (from digital media and cybersecurity to public policy, social research, and technology development), enabling the application of AI and network analysis to practical solutions for complex social challenges. This project will equip the candidate with expertise in applying AI and graph-based models to understand the dynamics of online social networks. Key research directions include modelling social dynamics, analysing online threats and misbehaviour, understanding the societal impact of social network algorithms, exploring generative AI and its misuse, and developing explainable AI for transparent and interpretable models. Situated at the intersection of AI, data science, and social computing, the research provides hands-on experience in graph and complex systems analysis, machine learning, and knowledge representation. The candidate will gain the skills to design strategies that mitigate harmful dynamics while supporting positive outcomes, including community engagement, open discourse, and public trust.

How to apply

Formal applications can be submitted via the University of Bradford web site. Applicants should register an account, select 'Postgraduate Research' as the course type and use the keywords 'computer science'. Please include the project title on the Research Proposal section; applicants are not required to supply a research proposal for this project.

Informal enquiries are also welcome.