Depression Detection in Social Media Comments Data Using Machine Learning Algorithms

dc.contributor.authorVasha, Zannatun Nayem
dc.contributor.authorSharma, Bidyut
dc.contributor.authorEsha, Israt Jahan
dc.contributor.authorNahian, Jabir Al
dc.contributor.authorPolin, ohora Akter
dc.date.accessioned2024-05-15T06:00:40Z
dc.date.available2024-05-15T06:00:40Z
dc.date.issued2023-04-15
dc.description.abstractDepression 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).
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/12340
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/12340
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.sourceDIU Institutional Repository
dc.subjectDepression, mental
dc.subjectSocial media
dc.subjectMachine learning
dc.subjectAlgorithms
dc.titleDepression Detection in Social Media Comments Data Using Machine Learning Algorithms
dc.typeArticle

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