Analysis of Breast Cancer Information on Facebook Using Neural Network-Based Topic Modeling and Metadata Analysis of English and Spanish Content: Comparative Study.

ABSTRACT:

Background

Breast cancer is the most common cancer diagnosis among women, with approximately 2.3 million new cases annually. When faced with a cancer diagnosis, individuals often turn to the internet for information or reassurance, despite the risk of encountering low-quality or incorrect information. While this observation is well documented in English, limited work has been done to understand the quality of breast cancer information in Spanish, the second most commonly spoken language in the United States.

Objective

This study uses natural language processing methods and quantitative modeling to analyze English and Spanish breast cancer posts from Facebook, a vital source of health-related information for 40% of English-speaking and 60% of Spanish-speaking adults in the Un

SUBMITTER: Muralidharan R 

PROVIDER: S-EPMC12572747 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature