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Utilizing Large Language Models to Monitor Social Media for Disability: An Analysis of Sentiment and Disability
Abdul Hamid Dabboussi1, Iman Yousuf2, Hannah Bullock3
1Lassonde School of Engineering, York University, Toronto, Canada.
Abstract:
This study explores how well large language models (like the kind that powers ChatGPT) can analyze online conversations about disability rights. We specifically looked at whether these models could: 1) identify if tweets about people with disabilities were positive or negative, and 2) tell if the tweets viewed disability as a problem with society (social model) or a problem with the individual (medical model). We collected 5,000 tweets and trained a language model to analyze them. The results demonstrated promising accuracy levels for sentiment analysis and social vs. medical model classification.
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