About the Project
Supervisor: Dr Giacomo Livan (UCL, Department of Computer Science)
Location: London, UK
About the project
Opinion dynamics is a fast growing interdisciplinary research area where problems of fundamental importance to our societies are studied with a mix of data-driven approaches and mathematical modelling.
The focus of this PhD will be that of developing quantitative approaches aimed at modeling and contrasting the diffusion of “fake news” and misinformation in online social networks (OSNs), which have been the subject of major research efforts in recent years. As the literature on the subject has grown, an apparent gap has emerged between its two main branches. On the one hand, increasingly sophisticated mathematical models have been put forward to understand how different rules of communication between individuals may lead to very different states (e.g., consensus, polarisation) in networked populations. On the other hand, data-driven studies have revealed a number of stylised facts that characterise the diffusion of information in the most popular OSNs, such as Facebook and Twitter. Yet, there is very little overlap between these two strands of research, as the currently available mathematical models struggle to come up with testable predictions, which in turn prevents from any meaningful model validation/rejection against empirical data. The focus of this PhD will be that of filling this gap by leveraging agent-based modelling and the wide array of existing techniques to calibrate agent-based models (ABMs) on empirical data. The candidate will design, simulate and – whenever possible – solve analytically ABMs of populations exchanging information via networks of relationships, incorporating a variety of cognitive biases (e.g., confirmation bias, motivated reasoning) in the agents’ behaviour and rules of communication. The calibration and validation of ABMs has been incredibly successful in a variety of fields, where it has ultimately allowed researchers to design models that deliver accurate predictions of the aggregate behaviour of extremely complex systems (e.g., the housing market). This approach can be expected to be equally successful in the context of opinion dynamics, where it will help to simulate and anticipate the consequences of misinformation attacks, and to design counterstrategies to neutralise them.
Applications are invited for a funded 4-year PhD studentship at the UCL Department of Computer Science, starting September 2021 under the supervision of Dr Giacomo Livan. Applicants should have:
· A BSc or MSc degree in Mathematics, Computer Science, Physics or related fields with top marks
· Experience with numerical simulations and scientific computing
· Strong mathematical background
· Good communication skills, especially in written English
· Strong work ethic and ability to think creatively and independently but also to work with a team
· Strong interest in interdisciplinary work
How to apply
Interested candidates are encouraged to contact Dr Giacomo Livan before submitting an application ([Email Address Removed]), with a CV and a short paragraph about their research interests. A complete formal application must be submitted via UCL Select no later than May 31st, 2021 (please email Dr Giacomo Livan your application number once submitted). Detailed information about the programme and how to apply can be found at:
Funding and eligibility
The studentship is funded by the Engineering and Physical Sciences Research Council (EPSRC) doctoral training partnership programme. Funding will be for 4 years, with a tax-free stipend of approximately £18,600k per year plus home-level university fees and additional funding to cover travel and training. Eligible candidates are UK nationals that meet residency requirements, EU nationals with settled status, EU nationals with pre-settled status that meet residency requirements, Irish nationals living in UK or Ireland, those who have indefinite leave to remain or enter. There is an option of a highly competitive top-up award for exceptional international candidates, so please get in touch to discuss your particular situation.
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