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According to the World Health Organization (WHO), approximately 1.4 millionindividuals died by suicide in 2022. This means that one person dies by suicideevery 20 seconds. Globally, suicide ranks as the 10th leading cause of death,while it ranks second for young people aged 15-29. In the year 2022, it wasestimated that about 10.5 million suicide attempts occurred. The WHO suggeststhat alongside each completed suicide, there are many individuals who makeattempts. Today, social media is a place where people share their feelings,such as happiness, sadness, anger, and love. This helps us understand how theyare thinking or what they might do. This study takes advantage of thisopportunity and focuses on developing an automated tool to find if someone maybe thinking about harming themselves. It is developed based on theSuicidal-Electra model. We collected datasets of social media posts, processedthem, and used them to train and fine-tune the model. Upon evaluating therefined model with a testing dataset, we consistently observed outstandingresults. The model demonstrated an impressive accuracy rate of 93% and acommendable F1 score of 0.93. Additionally, we developed an API enablingseamless integration with third-party platforms, enhancing its potential forimplementation to address the growing concern of rising suicide rates.

An Automated Tool to Detect Suicidal Susceptibility from Social Media Posts