Title | Survey of depression detection using social networking sites via data mining |
Publication Type | Conference Proceedings |
Year of Conference | 2020 |
Authors | Zafar, A., and S. R. Chitnis |
Conference Name | 10th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2020 |
Pagination | 88 - 93 |
Date Published | 2020 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN Number | 9781728127910 (ISBN) |
Keywords | Computer 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. |
DOI | 10.1109/Confluence47617.2020.9058189 |
Short Title | Proc. Conflu. - Int. Conf. Cloud Comput., Data Sci. Eng. |