Identifying Social Networks that Promote Desirable Outcomes

The field of opinion dynamics is concerned with modelling the ways in which people change their opinions within a society. A commonly studied question is "Under what conditions do all the agents in the network converge to an opinion?
And when is that final opinion the truth?"[1,2]. This project studies models of opinion diffusion under the lens of an outside agent that aims to manipulate the opinion that the network reaches. The topic of manipulation in social networks has already been looked at by this project's supervisor [3], with the aim of creating an accurate network-based approach for review aggregation. Within the non-Bayesian DeGroot model, the idea of a "Wise" society is well established as a network structure that becomes more likely to converge to the truth as it grows in size [1]. It is well understood that a size can only be wise if the influence of every individual agent tends to 0 as the population grows. Specific cases of manipulators making a society un-wise were studied in [4]. This paper was limited to looking at binary opinions and left open the question of what makes any given network robust against manipulation.
Determine what proportion of a given "wise" society's agents a manipulator needs to change in order to make the society un-wise. Identify what manipulation strategies can most effectively disrupt a wise network. Strategies include changing initial opinion, adding/removing social links and adding false agents. Identify network structures that minimise the impact of manipulation strategies.
A goal of this project is to tie the core mathematics underlying the DeGroot model (and possibly more social learning models) to the real world using data and case studies. We want to find out if pure mathematical solutions to
manipulation of networks can produce real-world solutions.
In the real world, agents often try to manipulate social networks for their own personal gains. The Oxford internet institute's 2020 survey [1] found evidence of political social media manipulation in every one of the 80+ countries it surveyed.
The results of this project could lead to non-invasive adjustments and changes that social networks could make to reduce the impact of these forms of manipulation. This can help companies to prevent spread of fake news on their
networks, whilst reducing the risk of losing their user-base by being too restrictive. This work could help avoid future incidents similar to the mass-exit of "Stop the Steal" conspiracy believers from social media that was trying to
crack down on fake news, to apps like Parlor, that promoted free-speech with little regulation. [2]
This project fits in very well with the CDTs work on Socio-technical systems. The work touches upon several research topics within the EPSRC remit: Complexity science, Human communication in ICT and Operational Research.

Research areas; Digital Economy
External Partner; TWS Partners

In the 2018 Government Office for Science report, 'Computational Modelling: Technological Futures', Greg Clarke, the Secretary of State for Business Energy and Industrial Strategy, wrote "Computational modelling is essential to our future productivity and competitiveness, for businesses of all sizes and across all sectors of the economy". With its focus on computational models, the mathematics that underpin them, and their integration with complex data, the MathSys II CDT will generate diverse impacts beyond academia. This includes impacts on skills, on the economy, on policy and on society.

Impacts on skills.
MathSys II will produce a minimum of 50 PhD graduates to support the growing national demand for advanced mathematical modelling and data analysis skills. The CDT will provide each of them with broad core skills in the MSc, a deep knowledge of their chosen research specialisation in the PhD and a complementary qualification in transferable skills integrated throughout. Graduates will thus acquire the profiles needed to form the next generation of leaders in business, government and academia. They will be supported by an integrated pastoral support framework, including a diverse group of accessible leadership role models. The cohort based environment of the CDT provides a multiplier effect by encouraging cohorts to forge long-lasting professional networks whose value and influence will long outlast the CDT itself. MathSys II will seek to maximise the influence of these networks by providing topical training in Responsible Research and Innovation, by maintaining a robust Equality, Diversity & Inclusion policy, and by integration with Warwick's global network of international partnerships.

Economic impacts.
The research outputs from many MathSys II PhD projects will be of direct economic value to commercial, public sector and charitable external partners. Engagement with CDT partners will facilitate these impacts. This includes co-supervision of PhD and MSc projects, co-creation of Research Study Groups, and a strong commitment to provide placements/internships for CDT students. When commercial innovations or IP are generated, we will work with Warwick Ventures, the commercial arm of the University of Warwick, to commercialise/license IP where appropriate. Economic impact may also come from the creation of new companies by CDT graduates. MathSys II will present entrepreneurship as a viable career option to students. One external partner, Spectra Analytics, was founded by graduates of the preceding Complexity Science CDT, thus providing accessible role models. We will also provide in-house entrepreneurship training via Warwick Ventures and host events by external start-up accelerator Entrepreneur First.

Impacts on policy.
The CDT will influence policy at the national and international level by working with external partners operating in policy. UK examples include Department of Health, Public Health England and DEFRA. International examples include World Health Organisation (WHO) and the European Commission for the Control of Foot-and-mouth Disease (EuFMD). MathSys students will also utilise the recently announced UKRI policy internships scheme.

Impacts on society.
Public engagement will allow CDT students to promote the value of their research to society at large. Aside from social media, suitable local events include DataBeers, Cafe Scientifique, and the Big Bang Fair. MathSys will also promote a socially-oriented ethos of technology for the common good. Concretely, this includes the creation of open-source software, integration of software and data carpentry into our computational and data driven research training and championing open-access to research. We will also contribute to the 'innovation culture and science' strand of Coventry's 2021 City of Culture programme.