Depression Detection on Social Media with the Aid of Machine Learning Platform: A Comprehensive Survey

G. Gupta, D. Sharma
{"title":"Depression Detection on Social Media with the Aid of Machine Learning Platform: A Comprehensive Survey","authors":"G. Gupta, D. Sharma","doi":"10.1109/INDIACom51348.2021.00116","DOIUrl":null,"url":null,"abstract":"Depression is a group of mental disorders associated with certain factors which can affect the mood, feelings, negativity, losing interest, and sadness in human participants. To maintain the quality of life, people tend to experience fewer mental health issues. Today social media is a major part of our daily life and these social media sites offer an important platform to share their emotions, feelings in day-to-day routine and life events. In recent years, automatic depression detection on social media-related studies has improved. The objective of this paper is to identify the different machine learning algorithm methods, techniques, and approaches used by various studies related to depression detection on social media platforms by conducting a comprehensive review. Various studies of from year 2013 to 2020 are reviewed to explore the research gaps and future directions.","PeriodicalId":415594,"journal":{"name":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 8th International Conference on Computing for Sustainable Global Development (INDIACom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIACom51348.2021.00116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Depression is a group of mental disorders associated with certain factors which can affect the mood, feelings, negativity, losing interest, and sadness in human participants. To maintain the quality of life, people tend to experience fewer mental health issues. Today social media is a major part of our daily life and these social media sites offer an important platform to share their emotions, feelings in day-to-day routine and life events. In recent years, automatic depression detection on social media-related studies has improved. The objective of this paper is to identify the different machine learning algorithm methods, techniques, and approaches used by various studies related to depression detection on social media platforms by conducting a comprehensive review. Various studies of from year 2013 to 2020 are reviewed to explore the research gaps and future directions.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于机器学习平台的社交媒体抑郁检测:一项综合调查
抑郁症是一组与某些因素相关的精神障碍,这些因素会影响人类参与者的情绪、感觉、消极情绪、失去兴趣和悲伤。为了保持生活质量,人们倾向于较少经历心理健康问题。今天,社交媒体是我们日常生活的重要组成部分,这些社交媒体网站提供了一个重要的平台来分享他们在日常生活和生活事件中的情绪、感受。近年来,社交媒体相关研究中的抑郁自动检测有所改进。本文的目的是通过进行全面的审查,确定与社交媒体平台上的抑郁症检测相关的各种研究中使用的不同机器学习算法、技术和方法。回顾了2013年至2020年的各种研究,探讨了研究的空白和未来的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Stochastic Scheduling of Parking Lot Operator in Energy and Regulation Markets amalgamating PBDR Social Synchrony: An Analytical Contemplation of Contemporary State of Art Frameworks The AI enabled Chatbot Framework for Intelligent Citizen-Government Interaction for Delivery of Services Biometric System - Challenges and Future Trends Solving SIS Epidemic Disease Model by Flower Pollination Algorithm
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1