Public Health Discussions on Social Media: Evaluating Automated Sentiment Analysis Methods.

ABSTRACT:

Background

Sentiment analysis is one of the most widely used methods for mining and examining text. Social media researchers need guidance on choosing between manual and automated sentiment analysis methods.

Objective

Popular sentiment analysis tools based on natural language processing (NLP; VADER [Valence Aware Dictionary for Sentiment Reasoning], TEXT2DATA [T2D], and Linguistic Inquiry and Word Count [LIWC-22]), and a large language model (ChatGPT 4.0) were compared with manually coded sentiment scores, as applied to the analysis of YouTube comments on videos discussing the opioid epidemic. Sentiment analysis methods were also examined regarding ease of programming, monetary cost, and other practical considerations.

Methods

Evaluation methods included descriptive s

SUBMITTER: Gandy LM 

PROVIDER: S-EPMC11784633 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature