DSpace Repository

Depression Detection in Social Media Comments Data Using Machine Learning Algorithms

Show simple item record

dc.contributor.author Vasha, Zannatun Nayem
dc.contributor.author Sharma, Bidyut
dc.contributor.author Esha, Israt Jahan
dc.contributor.author Nahian, Jabir Al
dc.contributor.author Polin, ohora Akter
dc.date.accessioned 2024-05-15T06:00:40Z
dc.date.available 2024-05-15T06:00:40Z
dc.date.issued 2023-04-15
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/12340
dc.description.abstract 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). en_US
dc.language.iso en_US en_US
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.subject Depression, mental en_US
dc.subject Social media en_US
dc.subject Machine learning en_US
dc.subject Algorithms en_US
dc.title Depression Detection in Social Media Comments Data Using Machine Learning Algorithms en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Browse

My Account

Statistics