Phd Studentship: Using Natural Language Processing And Computer Vision To Understand Representation Of Climate Change In Popular Media

Exeter, United Kingdom

Job Description


Location

Centre for Doctoral Training in Environmental Intelligence, Streatham Campus, Exeter

The University of Exeter\'s Centre for Doctoral Training in Environmental Intelligence, is inviting applications for a PhD studentship funded by Children\'s Investment Facilitation Fund to commence in September 2023. The successful applicant will join the UKRI CDT in Environmental Intelligence, and will be included in CDT cohort building and training activities.

Project Description

This PhD will apply data science techniques including machine learning, natural language processing and computer vision to rich data collected from popular media of different kinds. The media plays a significant role in shaping and reflecting societal attitudes and beliefs, including for the representation and public perception of climate change and environmental issues. This interdisciplinary research project will draw from a diversity of disciplines, including data science, geography, and media and journalism studies. The project will go beyond the status quo in climate communications research (which tends to focus on newspaper studies or social media research) to focus on television as a significant source of information and influence in the climate debate; and a key point of potential intervention for reaching beyond the already-engaged. The project will explore and critique a diverse range of televisual content and styles: from soaps and drama (e.g. Eastenders), to chat shows (such as Top Gear), to anime.

This project will employ methods from data mining, natural language processing, and computer vision to examine the prevalence and context of various tropes in popular media, building upon existing work on how climate change is framed in news media, both textually and visually. It aims to develop a nuanced understanding of environmental narratives and their implications in shaping societal perceptions and attitudes towards climate change.

The primary methodological approach will involve using data science techniques to analyse large datasets such as TVTropes, Box of Broadcasts (BoB), and other popular media databases, ranging from television to films and Netflix. This will include building and analysing networks of tropes, authors, and media, and studying the evolution of environmental narratives in these networks. Additionally, the project will explore the possibility of developing a monitoring tool to track the alignment of shows with actual or proposed policy actions on climate and environment.

The project will be conducted in collaboration with key industry partners, providing the opportunity for real-world impact and application of research findings. This approach will foster a comprehensive understanding of the varied techniques and approaches used in the project.

We envisage that you will actively engage in the project, presenting your findings at international workshops and conferences, and publishing your research in peer-reviewed journals.

Eligibility

This award is open to applicants eligible for \'Home\' and \'International\' fee status. International applicants need to be aware that you will have to cover the cost of your student visa, healthcare surcharge and other costs of moving to the UK to do a PhD.

The closing date for applications is midnight on Monday 31st July 2023. Interviews are TBC

Summary

Application Deadline: 31 July 2023

Value: Home fees plus annual tax-free stipend of at least \xc2\xa318,622 in year 1. \xc2\xa310,000 project budget for research and training.

Duration of award: 4 years

Contact:

For further information or to apply click here -

From \xc2\xa318,622 per year

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Job Detail

  • Job Id
    JD2977737
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    £18622 per year
  • Employment Status
    Permanent
  • Job Location
    Exeter, United Kingdom
  • Education
    Not mentioned