基于数据挖掘的社交网站抑郁检测调查

Aqsa Zafar, Dr. Sanjay Chitnis
{"title":"基于数据挖掘的社交网站抑郁检测调查","authors":"Aqsa Zafar, Dr. Sanjay Chitnis","doi":"10.1109/Confluence47617.2020.9058189","DOIUrl":null,"url":null,"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.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Survey of Depression Detection using Social Networking Sites via Data Mining\",\"authors\":\"Aqsa Zafar, Dr. Sanjay Chitnis\",\"doi\":\"10.1109/Confluence47617.2020.9058189\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":180005,\"journal\":{\"name\":\"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/Confluence47617.2020.9058189\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Confluence47617.2020.9058189","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21

摘要

在过去的几年里,人们对社交网站的抑郁检测进行了广泛的研究。这些网站为用户提供了一个分享生活事件、情感和日常事务的平台。许多研究表明,用户生成的内容是了解其心理状态的有效途径。通过挖掘用户生成的内容,可以预测抑郁症。通过从社交网站的帖子中收集所有必要和相关的信息,我们可以预测这个人的情绪或消极情绪。这篇调查论文的重点是关于基于社交网站内容检测抑郁程度的先前研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Survey of Depression Detection using Social Networking Sites via Data Mining
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信