Big data analytics on social networks to detect melancholy in real-time

During the coronavirus pandemic, wide variety of despair instances has dramatically increased. Several melancholy sufferers disclose their true feeling with aid social media. Thus, large records analytics on networks for real-time detection is proposed. Machine mastering techniques were utilized as mannequin construction. There are five computing device strategies explored in this research which Support Vector Machine, Decision Tree, Naïve Bayes, Random Forest, and Deep Learning. The experimental outcomes revealed that Forest technique performed higher accuracy than other methods to become aware depression. Keywords: Big data analytics, Depression detection,