Online communities are virtual spaces for users to share interests, support others, and for knowledge or information exchange. Understanding user behaviour is extremely useful for a variety of applications—from being able to tailor a marketing campaign through to identifying dangerous actors in a network. Here, we are looking for a PhD candidate to better understand the Anti-5G online communities and their role in current attacks on mobile network masts across the UK. This is an EPSRC-funded iCASE project linked with BT (formerly, British Telecom). The candidate will have a unique association with BT and access to extensive data regarding the Anti-5G movement. Due to the links with BT, the student would be expected to spend some time in Ipswich (UK) for additional training and experience.
There are a number of ways that we can learn about individual and group behaviour in online contexts. For this PhD project, we are drawing from social sciences for a theoretical grounding – for example, Social Identity Theory, Social Cognitive Theory – in order to make sense of big data from online communities such as Twitter, Reddit, or other specific forums. We are looking to use a variety of quantitative techniques to analyse these data, which might include (social) network analysis, machine learning techniques, and computational linguistics.
In summary, this PhD will focus on the following themes:
- Identifying types of role (e.g., leader, conversationalists, etc) within online communities – this might include analysing user interaction with the forum alongside analysing user linguistic styles
- Understanding the link between online and offline behaviour – for instance, as much of the context relates to Anti-5G narratives, working with BT, we will be able to consider the association between online discussions and reports of actual offline damage and whether this can be predicted in future
- Understanding how the Anti-5G narrative has changed over time – for example, have the topics changed? Have the way groups interact changed?
Candidates should have a solid grounding in theories of online behaviour, which will inform how we approach the research questions. It’s essential for the candidate to have an active interest in the digital technology space, and desirable to have good understanding of quantitative methods. We anticipate the candidate to attend a variety of summer and winter schools to learn new quantitative/digital methods, alongside time within BT for additional quantitative training.
How to apply
Applicants must submit a formal application, CVs will not be accepted. Guidance on how to apply for doctoral study at Bath can be found here: How to apply for doctoral study (bath.ac.uk). For questions about the research project, please contact the named supervisors through Advanced search — the University of Bath's research portal.
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in a social or computer science with a strong quantitative element. A relevant Master’s degree and/or experience in one or more of the following will be an advantage: computational or data science, natural language processing, R or R-Studio, Python or other coding language.
Preferred start date: 03 October 2022