International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Suicide Risk Prediction Using Text Based Pattern Recognition on Social Media |
|---|---|
| ABSTRACT | Social media platforms have become common spaces where individuals express their emotions and mental health concerns. Identifying suicidal ideation from such textual content is crucial for early prevention and support. This paper presents a transformer-based suicide risk prediction system using publicly available Reddit posts. Light text preprocessing is applied to preserve contextual and emotional meaning within the data. The ALBERT transformer model is employed for binary classification of suicidal and non-suicidal posts. Experimental results indicate that the proposed approach outperforms traditional machine learning methods, achieving an accuracy of approximately 80%. The study emphasizes the importance of context-aware modeling for effective suicide risk identification and ethical prevention. |
| AUTHOR | DIVYA DHARSHINI J, DINESH P, PREETHI M Student, Dept. of B.Sc. Computer Science with Data Analytics, Dr. N.G.P Arts and Science, Coimbatore, India Guide, Dept. of B.Sc. Computer Science with Data Analytics, Dr. N.G.P Arts and Science, Coimbatore, India |
| VOLUME | 182 |
| DOI | DOI: 10.15680/IJIRCCE. 2026.1403110 |
| pdf/110_Suicide Risk Prediction Using Text Based Pattern Recognition on Social Media.pdf | |
| KEYWORDS | |
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