Detecting and Characterizing Trends in Online Mental Health Discussions

被引:9
作者
Chakravorti, Dante [1 ]
Law, Kathleen [2 ]
Gemmell, Jonathan [3 ]
Raicu, Daniela [3 ]
机构
[1] Univ Calif Irvine, Donald Bren Sch, ICS, Irvine, CA 92697 USA
[2] Worcester State Univ, Dept Comp Sci, Worcester, MA USA
[3] Depaul Univ, Sch Comp, Chicago, IL 60604 USA
来源
2018 18TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW) | 2018年
基金
美国国家科学基金会;
关键词
D O I
10.1109/ICDMW.2018.00107
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Mental illness is a widespread public health concern that affects many individuals on a daily basis. Increasingly, people are turning to social media to discuss their mental health. The result is a rich dataset of authentic discussions from which to draw insights. In this work, we collected data from multiple mental health forums on the popular social media website, Reddit. We extracted topics from these datasets and then observed the trends of these topics from 2012 to 2018. These trends fall into many recognizable patterns. Some trends are stable, often using common words found in mental health conversations. Other trends are increasing or decreasing. In this work, we found that topics with positive words are becoming less frequently used and topics with negative connotations are becoming more frequently used. Other trends display a periodic pattern, like those associated with the school year. One trend demonstrates a sudden shift in conversation possibly due to a change in how the site is administered. We confirm these qualitative observations through quantitative analysis with statistical tests.
引用
收藏
页码:697 / 706
页数:10
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