Using LLM to Understand Medication-Related Trends in Social Media

Project Member(s): Adams, J., Jiang, J., Long, G., Peng, X., Shen, T., Debono, D.

Funding or Partner Organisation: Commonwealth Department of Health and Aged Care (Department of Health and Ageing)
Digital Health CRC Limited (Digital Health CRC)
Digital Health CRC Limited (Digital Health CRC)

Start year: 2023

Summary: To address this problem, our project aims to develop a novel framework that employs LLM (or its equivalents, e.g., BARD, LLAMA), an advanced language model, to analyze and identify medication-related trends in social media content, particularly related to medicine shortages. The proposed solution will leverage ChatGPT's ability to understand natural language, context, and sentiment, enabling the identification and extraction of relevant information from social media data.

FOR Codes: Public health (excl. specific population health), Administration and business support services, Deep learning, Natural language processing, Data mining and knowledge discovery

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.