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  Online (mis)information and climate change: Using network analysis and machine learning to understand environmental debate PhD (Funded)


   College of Engineering, Mathematics and Physical Sciences

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  Dr H Williams  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

About the Award
An opportunity exists for a motivated student to undertake a PhD in Computer Science at the University of Exeter. The project is intended to have September 2018 start, with some flexibility in exceptional circumstances. A single studentship will be awarded to the best applicant.
For eligible students the studentship will cover UK/EU tuition fees plus an annual tax-free stipend of at least £14,777 (2017/18 rate) for 3.5 years, and a research training support grant.
The student will be based in Computer Science in the College of Engineering, Mathematics and Physical Sciences at the Streatham Campus in Exeter.

Academic Supervisors:
Dr Hywel Williams, University of Exeter

Project Description:
This data science PhD project will apply complex network analysis and machine learning to study the online media ecosystem around the contentious topic of climate change.
Despite widespread scientific consensus, climate change remains a controversial and politicised topic. On one side, environmentalists push for greater action to prevent and mitigate the effects of climate change. On the other, a well-funded climate denial lobby promote doubt and confuse public opinion. This debate is actively pursued in online news and social media, where denialist blogs and commentators attempt to discredit the scientific viewpoint with a steady stream of contrarian articles and social media posts.
Since many people now access news through online platforms and social media, and since climate change is a complex subject, there is significant potential for misinformation. So-called “fake news” has been much discussed in the context of politics, where it is argued to have a significant disruptive effect on public debate and electoral processes. Meanwhile, automated “bots” and managed social media accounts can be operated to spread a particular kind of content, promote a political view, or support/attack individuals. Even without deliberate manipulation, the networked nature of social media can lead to polarisation and highly biased flows of information. However, the extent of all these phenomena is unknown for climate change.
This PhD project will apply advanced computational methods to understand the online media ecosystem around climate change. In particular, it will seek to characterise the role of misinformation in online climate debates, looking in particular at social media accounts, bots and fake news sites linked to the climate denial viewpoint. Within this topic area there is considerable scope for the student to shape the project towards their own interests. The methods utilised will depend on the exact research question chosen, but are likely to combine complex network analysis, machine learning and text mining.
This project will require a strong mathematical and computational background. The large majority of the research will focus on development of computational tools to characterise, measure and visualise the complex dynamics of online media. Some understanding of online behaviour and climate change will help to position the research within its wider societal context. Therefore this project also requires a willingness to engage with interdisciplinary research, for example, relevant work in quantitative social sciences, communications science and environmental politics.
The project will suit a motivated student with a strong quantitative background (e.g. computer science, mathematics, physics) and an interest in how the Web is changing our society. The student will join a vibrant and growing research group focused on social & environmental data science, with affiliations to the Department of Computer Science and the newly formed Institute for Data Science & Artificial Intelligence at University of Exeter. The project offers exceptional opportunities for future employment in academic or commercial data science.

Funding for this project is confirmed, provided by University of Exeter, for a studentship of 3.5 years. This award provides annual funding to cover UK/EU tuition fees and a tax-free stipend. For students who pay UK/EU tuition fees the award will cover the tuition fees in full, plus at least £14,777 per year tax-free stipend. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee and no stipend. The studentship will be awarded on the basis of merit for 3.5 years of full-time study to commence in September 2018.

Interested students are encouraged to contact Dr Hywel Williams ([Email Address Removed]) to discuss their suitability.


Funding Notes

Entry requirements:
Applicants for this studentship must have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science or technology, e.g. computer science, mathematics, physics. Strong programming and mathematical ability is essential.
If English is not your first language you will need to have achieved at least 6.5 in IELTS and no less than 6.0 in any section by the start of the project. Alternative tests may be acceptable (see http://www.exeter.ac.uk/postgraduate/apply/english/).

Where will I study?