Social Influence on Individuals’ Choices: A Game-Theoretic Social Network Approach

The School of Mathematical Sciences of Queen Mary University of London invite applications for a PhD project commencing either in September 2018 for students seeking funding, or at any point in the academic year for self-funded students. The deadline for funded applications is the 31st of January 2018.

This project will be supervised by Professor Vito Latora and Professor Nejat Ambarci.

Individuals make many choices every day such as which cereal or book to buy, or movie to see or place to have lunch at. Some of these decisions can also be very important for their lives, such as which political candidate to support or university to attend or career to pursue. Many individuals tend to think that they are making these decisions purely on their own tastes and preferences,
without realizing they actually make their choices with a huge influence of others in almost every aspect of life. People vote because others do so, eat more when others eat, buy a new car because their neighbours or friends have recently done so. Thus, social influence affects the products people buy, health plans they choose, careers they follow, and shapes whether people save for retirement, invest in the stock market, donate money to charity, save energy, or adopt new innovations. It is indeed difficult to find a decision or choice that is not affected by other people. Thus, in a broad sense, the purpose of this PhD project is the combined use of game theory and complex networks theory to understand and model how social influence affects individuals’ choices/decisions.

The student will develop game theoretic models based on, but not limited to, the prisoner’s dilemma, the public good game and the trust game, and he will implement them within the setup of complex networks, especially networks with multiple layers and/or time-varying links. The focus will be on understanding how the network structure affects the nature of the outcomes of the games.
Different equilibrium concepts (Nash, subgame-perfect, Bayesian-Nash and perfect-Bayesian equilibria) will be used together with heterogeneous mean-field approaches to treat networks with scale-free degree distributions.

The mathematical framework will be instrumental to face some general problems (such as understanding cumulative culture through the explicit modelling of innovation processes, which may lead to different cultural repertoires of societies under different environments and environmental changes) and also to practical applications (such as proposing novel recommendation systems to improve those already used by global companies like Amazon or Netflix to increase their sales).

The perfect candidate will hold an MSc or an equivalent degree in applied mathematics or theoretical physics, and will have a good background in complex systems, network science, and experience with computer programming, numerical simulations as well as statistical analysis. Previous knowledge of game theory is also desirable.

The application procedure is described on the School website. For further inquiries please contact Professor Vito Latora at [Email Address Removed]. This project is eligible for full funding, including support for 3.5 years’ study, additional funds for conference and research visits and funding for relevant IT needs. Applicants interested in the full funding will have to participate in a highly competitive selection process.