@article{ref1,
title="Suicide possibility scale detection via Sina Weibo analytics: preliminary results",
journal="International journal of environmental research and public health",
year="2022",
author="Gu, Yun and Chen, Deyuan and Liu, Xiaoqian",
volume="20",
number="1",
pages="e466-e466",
abstract="Suicide, as an increasingly prominent social problem, has attracted widespread social attention in the mental health field. Traditional suicide clinical assessment and risk questionnaires lack timeliness and proactivity, and high-risk groups often conceal their intentions, which is not conducive to early suicide prevention. In this study, we used machine-learning algorithms to extract text features from Sina Weibo data and built a suicide risk-prediction model to predict four dimensions of the Suicide Possibility Scale-hopelessness, suicidal ideation, negative self-evaluation, and hostility-all with model validity of 0.34 or higher. Through this method, we can detect the symptoms of suicidal ideation in a more detailed way and improve the proactiveness and accuracy of suicide risk prevention and control.<p /> <p>Language: en</p>",
language="en",
issn="1661-7827",
doi="10.3390/ijerph20010466",
url="http://dx.doi.org/10.3390/ijerph20010466"
}