Using Natural Language Processing to Explore Social Media Opinions on Food Security: Sentiment Analysis and Topic Modeling Study.

ABSTRACT:

Background

Social media has the potential to be of great value in understanding patterns in public health using large-scale analysis approaches (eg, data science and natural language processing [NLP]), 2 of which have been used in public health: sentiment analysis and topic modeling; however, their use in the area of food security and public health nutrition is limited.

Objective

This study aims to explore the potential use of NLP tools to gather insights from real-world social media data on the public health issue of food security.

Methods

A search strategy for obtaining tweets was developed using food security terms. Tweets were collected using the Twitter application programming interface from January 1, 2019, to December 31, 2021, filtered for Australia-based user

SUBMITTER: Molenaar A 

PROVIDER: S-EPMC10995791 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature