文献类型： 会议论文
第一作者： Jayshri Suresh Sonawane
作者： Jayshri Suresh Sonawane 1 ; Dinesh Jain 1 ;
作者机构： 1.Dept. of Computer Science and Engineering, SAGE University, Indore, India
关键词： Deep learning;Machine learning algorithms;Accuracy;Social networking (online);Reviews;Feature extraction;Natural language processing;Distance measurement;Classification algorithms;Public healthcare
会议名称： IEEE World Conference on Applied Intelligence and Computing
主办单位：
页码： 1508-1512
摘要： In contemporary society, Suicide has become a notable concern within the realm of public health. Suicidal ideation (SI) encompasses thoughts about ending one's life. Factors contributing to suicidal thoughts and actions are diverse, ranging from personal life events to enduring emotional distress. We investigate the issue of identifying such ideation on Twitter, emphasizing the usefulness of a collection of characteristics taken from the literature as well as the function of discussion context in this process. Numerous machine learning algorithms have been put forth to identify SI from internet channels, but because feature engineering and classification techniques are still lacking, the accuracy of these algorithms is still low. Therefore, by using novel deep learning and natural language processing-based feature engineering technique accuracy can be increased.
分类号： tp3
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