Use of Large Language Models to Assess the Likelihood of Epidemics From the Content of Tweets: Infodemiology Study.

ABSTRACT:

Background

Previous work suggests that Google searches could be useful in identifying conjunctivitis epidemics. Content-based assessment of social media content may provide additional value in serving as early indicators of conjunctivitis and other systemic infectious diseases.

Objective

We investigated whether large language models, specifically GPT-3.5 and GPT-4 (OpenAI), can provide probabilistic assessments of whether social media posts about conjunctivitis could indicate a regional outbreak.

Methods

A total of 12,194 conjunctivitis-related tweets were obtained using a targeted Boolean search in multiple languages from India, Guam (United States), Martinique (France), the Philippines, American Samoa (United States), Fiji, Costa Rica, Haiti, and the Bahamas, coveri

SUBMITTER: Deiner MS 

PROVIDER: S-EPMC10943433 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature