Thematic Network Modelling for Digital Ecosystems

The contect of the research
The shift from traditional communication methods towards digital ones brings about massive information dissemination with little to no regulation, making difgital ecosystems and increasingly timely interdisciplinary topic in recent years. Digital ecosystems can include, for example social media platforms and digital markets. Understanding such systems and proposign appropriate policies have therefore become more and more prominent recently. Current computational techniques rarely pay attention to the inherent role each individual/organisation/company's behaviour plays in the ecology from a system-level perspective, such as information creator, propagandist and listener in the online social media, or crucial/peripheral rank each stakeholder posesesses in a digital market. This project therefore would like to build on such traits, especially in the context of multi-sided groups.
The aims and objectives of the research
This project aims at dveloping computational analysis, simulation and intervention of interaction dynamics in digital ecosystems, seeking to answer the following key problems;
1. How to assess the inherant role each individual/organisation. complay plays in a system-levale interpretable way.
2. Can we make meaningful comparison between milti-sided groups via thier role sturctures and behavioral simiulation.
3. To improv the digital ecosystem, what intervention approaches can be proposed based on the analysis above? This will likely make use to the reommendation algorithm.
4. What are the scalability limitations of the method above, and can we mitigate them to enable analysis on increasing data sizes (e.g across large population samples or different geographies)?
The novelty of the research methodology
The main novelty in this research is the application of network structure techniques to assess system-level collective behavioral features in digital ecosystems and propose relevant intervention approaches accordingly, particularly relevant with recmmendation algorithms.
The potential impact, applications and benefits
Introducing complex network structures to digital ecosystems can provide an intuitive system-level evaluation of extensive user interaction dynamics. Appropriate intervention methods may be explored to potentially improve digital regilation and policy.
How the rsearch relates to the remit
This research is closely related with the EPSRC remit in both its methodology and goal. Complex network modelling as the primary methodology strongly relies on mathematical sciences. The goal is to improve the digital ecosystem, lying in both Digital Economy and ICT (Inofrmation and Communication Technologies).
External Partner - StateUP (https://stateup.co/nebula/) - StateUp is a start up company which stands at the crossroads of industry and academia, working on procurement technologies for the publc sector. It will provide me with both internship opportunities and datasets. In details, I can help build Nebula, a repository curated by stateUp that can be used to make recommendations to public bodies seeeking to resolve societal problems at various scales. During this process, I will also have exclusive access to acurated dataser of company profiles.

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.