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Survey of depression detection using social networking sites via data mining

TitleSurvey of depression detection using social networking sites via data mining
Publication TypeConference Proceedings
Year of Conference2020
AuthorsZafar, A., and S. R. Chitnis
Conference Name10th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2020
Pagination88 - 93
Date Published2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN Number9781728127910 (ISBN)
KeywordsComputer Science and Engineering, Scopus
Abstract

Depression detection from Social Networking sites has been studied broadly in previous years. These sites provide a platform for their users to share their life events, emotions, and everyday routine. Many researchers demonstrated that content generated by the users is an efficient way to know about their mental state. By mining user-generated content, depression can be predicted. By collecting all the necessary and relevant information from the social networking sites from the posts, we can predict the person's mood or negativity. This survey paper focuses on prior research done regarding detecting depression levels based on content from social network sites. © 2020 IEEE.

DOI10.1109/Confluence47617.2020.9058189
Short TitleProc. Conflu. - Int. Conf. Cloud Comput., Data Sci. Eng.