AUTHOR=Li Ang 

TITLE=Predicting negative attitudes towards suicide in social media texts: prediction model development and validation study

JOURNAL=Frontiers in Public Health

VOLUME=Volume 12 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2024.1401322

DOI=10.3389/fpubh.2024.1401322

ISSN=2296-2565

ABSTRACT=Background: Implementing machine learning prediction of negative attitudes towards suicide may improve health outcomes. However, in previous studies, varied forms of negative attitudes were not adequately considered, and developed models lacked rigorous external validation. By analyzing a large-scale social media dataset (Sina Weibo), this paper aims to fully cover varied forms of negative attitudes and develop a classification model for predicting negative attitudes as a whole, and then to externally validate its performance on population and individual levels. Methods: 938866 Weibo posts with relevant keywords were downloaded, including 737849 posts updated between