WITHDRAWN: Depression detection using data mining algorithms from social media context

Depression is the next level of negative emotions. When a person is in a sad mood or going through a difficult situation and it is not leaving him and giving him pain continuously and he is unable to bear it anymore, that situation is called depression. The last stage of depression occurs in suicide. According to the World Health Organization (WHO), Currently, 4.4% of people in the world are currently suffering from depression. In 2021, fourteen thousand people committed suicide all over the world and the rating of suicide is increasing day by day. So, our study is to find depressed people by their comments, posts, or texts on social media. We collected almost 10,000 data from Facebook posts, comments, and YouTube comments. Data mining and machine learning (ML) algorithms make our work easier and play a big role in easily detecting a person’s emotions. We applied six classifiers to predict depression non-depression and found the best accuracy on a support vector machine (SVM).

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“…The SVM is also known as SVM which is a non-probabilistic linear binary classifier [22]. It is normally used to recognize or detect any problems.…”

Section: Support Vector Machinementioning

confidence: 99%

“…They applied classifiers and used different tools to recognize depression. Tummala et al [22] have used ML calculations like SVM, random forest (RF), logistic regression (LR), and NB. They collected huge data from Facebook comments, depressed and nondepressed Reddit posts, Reddit users, and Twitter.…”

Section: Introductionmentioning

confidence: 99%