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News Implied Climate Sentiment through NLP and Data Correlation Analysis
Scholarship details
| Study levels | Degree |
|---|---|
| Close date | Monday, 22 September 2025 |
| Domestic/international | Domestic Only |
About the scholarship
This project utilizes cutting-edge AI tools to examine the relationship between news-implied climate sentiment and economic behaviour. You'll work with three datasets: (1) climate change articles, (2) climate reports, and (3) official economic reports. Using Natural Language Processing (NLP) and Large Language Models (LLMs), you'll build tools to measure the climate sentiment and study how it is related to other factors. You will gain hands-on experience with Python NLP tools and LLMs, skills in data scraping, preprocessing, and cross-domain text analysis, exposure to interdisciplinary research at the intersection of AI, climate science, and economics, and the chance to co-author a research paper or technical report.
Entry requirements
A completed online application must be submitted by 4:30 pm on the closing date. Any required supporting documentation (including references) must also be received by the closing date in order for the application to be considered.