ArticleInternational journal of environmental research and public health2022
Detecting Suicidal Ideation in Social Media: An Ensemble Method Based on Feature Fusion.
Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Article
- Digital Detection of Suicidal Ideation: A Scoping Review to Inform Prevention and Psychological Well-Being.Behavioral sciences (Basel, Switzerland) · 2025Review
- Deep Learning-Based Detection of Depression and Suicidal Tendencies in Social Media Data with Feature Selection.Behavioral sciences (Basel, Switzerland) · 2025Article
- Mining Suicidal Ideation in Chinese Social Media: A Dual-Channel Deep Learning Model with Information Gain Optimization.Entropy (Basel, Switzerland) · 2025Article
- Explainable AI-based suicidal and non-suicidal ideations detection from social media text with enhanced ensemble technique.Scientific reports · 2025Article
- Apriori algorithm based prediction of students' mental health risks in the context of artificial intelligence.Frontiers in public health · 2025Article
- Neural activity during inhibitory control predicts suicidal ideation with machine learning.NPP - digital psychiatry and neuroscience · 2024Article
- Mind4Health: decolonizing gatekeeper trainings using a culturally relevant text message intervention.Frontiers in public health · 2024Article
- Exploring suicide ideation in university students: sleep quality, social media, self-esteem, and barriers to seeking psychological help.Frontiers in psychiatry · 2024Article
- The effects of short video app-guided loving-kindness meditation on college students' mindfulness, self-compassion, positive psychological capital, and suicide ideation.Psicologia, reflexao e critica : revista semestral do Departamento de Psicologia da UFRGS · 2023Article
- Linguistic Analysis for Identifying Depression and Subsequent Suicidal Ideation on Weibo: Machine Learning Approaches.International journal of environmental research and public health · 2023Article
- Suicide Possibility Scale Detection via Sina Weibo Analytics: Preliminary Results.International journal of environmental research and public health · 2022Article
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Authors and funding
3 authors.
Funding
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Abstract
Suicide has become a serious problem, and how to prevent suicide has become a very important research topic. Social media provides an ideal platform for monitoring suicidal ideation. This paper presents an integrated model for multidimensional information fusion. By integrating the best classification models determined by single and multiple features, different feature information is combined to better identify suicidal posts in online social media. This approach was assessed with a dataset formed from 40,222 posts annotated by Weibo. By integrating the best classification model of single features and multidimensional features, the proposed model ((BSC + RFS)-fs, WEC-fs) achieved 80.61% accuracy and a 79.20% F1-score. Other representative text information representation methods and demographic factors related to suicide may also be important predictors of suicide, which were not considered in this study. To the best of our knowledge, this is the good try that feature combination and ensemble algorithms have been fused to detect user-generated content with suicidal ideation. The findings suggest that feature combinations do not always work well, and that an appropriate combination strategy can make classification models work better. There are differences in the information contained in different functional carriers, and a targeted choice classification model may improve the detection rate of suicidal ideation.
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