Facebook Social Media for Depression Detection in the Thai Community

Kantinee Katchapakirin, K. Wongpatikaseree, P. Yomaboot, Y. Kaewpitakkun
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引用次数: 45

Abstract

Depression is one of the leading mental health problems. It is a cause of psychological disability and economic burden to a country. Around 1.5 Thai people suffer from depression and its prevalence has been growing up fast. Although it is a serious psychological problem, less than a half of those who have this emotional problem gained access to mental health service. This could be a result of many factors including having lack awareness about the disease. One of the solutions would be providing a tool that depression could be easily and early detected. This would help people to be aware of their emotional states and seek help from professional services. Given Facebook is the most popular social network platform in Thailand, it could be a largescale resource to develop a depression detection tool. This research employs Natural Language Processing (NLP) techniques to develop a depression detection algorithm for the Thai language on Facebook where people use it as a tool for sharing opinions, feelings, and life events. Results from 35 Facebook users indicated that Facebook behaviours could predict depression level.
Facebook社交媒体在泰国社区检测抑郁症
抑郁症是主要的心理健康问题之一。它是造成一个国家心理残疾和经济负担的原因。大约有1.5名泰国人患有抑郁症,其患病率一直在快速增长。虽然这是一个严重的心理问题,但只有不到一半的有这种情绪问题的人获得了心理健康服务。这可能是许多因素造成的,包括对这种疾病缺乏认识。其中一个解决方案是提供一种工具,可以很容易地及早发现抑郁症。这将有助于人们意识到自己的情绪状态,并寻求专业服务的帮助。鉴于Facebook是泰国最受欢迎的社交网络平台,它可能是开发抑郁症检测工具的大量资源。这项研究采用自然语言处理(NLP)技术,为Facebook上的泰语开发了一种抑郁症检测算法,人们将其作为分享观点、感受和生活事件的工具。对35名Facebook用户的调查结果表明,Facebook行为可以预测抑郁程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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