DocumentCode :
695400
Title :
Social Media, Big Data, and Public Health Informatics: Ruminating Behavior of Depression Revealed through Twitter
Author :
Nambisan, Priya ; Zhihui Luo ; Kapoor, Akshat ; Patrick, Timothy B. ; Cisler, Ron A.
fYear :
2015
fDate :
5-8 Jan. 2015
Firstpage :
2906
Lastpage :
2913
Abstract :
Undiagnosed and untreated depressive disorders have become a serious public health issue and it is prevalent among people of all ages, gender and race. Social media sites, such as Twitter, have become a major venue for people to express/disclose their thoughts and feelings. The tweets from these micro-blogging sites could be used to screen for and potentially detect depression. To date, studies in this area have focused on developing and validating the terms and vocabulary used by users with depression, or evaluating tweets related to depression by using terms that are synonymous with depression. This approach has not produced reliable findings. In this study, we depart from this approach and instead, base our analysis on research on depressive disorders, which indicates the critical significance of repetitive thoughts and ruminating behavior of people with depression. The current study and findings hold important implications for research on depression, social media, and public health informatics.
Keywords :
Big Data; medical information systems; patient diagnosis; social networking (online); social sciences computing; Twitter; Undiagnosed depressive disorders; big data; depression behavior; depression related tweets; microblogging sites; public health informatics; public health issue; social media; untreated depressive disorders; Media; Mood; Pain; Public healthcare; Sociology; Statistics; Twitter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Sciences (HICSS), 2015 48th Hawaii International Conference on
Conference_Location :
Kauai, HI
ISSN :
1530-1605
Type :
conf
DOI :
10.1109/HICSS.2015.351
Filename :
7070166
Link To Document :
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