Abstract
The increase use of social media allows unprecedented access to the behaviors, thoughts and feelings of individuals. We are interested here in the evolution of the emotional states of individuals captured through microblogging services such as Twitter. According to the World Health Organization (WHO) report in 2016, around 800,000 of individuals have committed suicide. Suicide is a major health concern worldwide. Our objective was to produce a new algorithm inspired by the spotted hyenas life (SHO) to detect person in suicide situation through the analysis of the twitter social network. So in this paper, we propose our approach to prediction suicidal tweets that can be published by people who suspect by their suicidal intentions. The proposed algorithm gives better performance compared to machine learning algorithms such as Naïve Bayes (NB), K-Nearest Neighbors (KNN), the Decision Tree (DT) and Support Vector Machine (SVM).
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