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http://dspace.aiub.edu:8080/jspui/handle/123456789/1673
Title: | Identifying insomnia from social media posts: psycholinguistic analyses of user tweets |
Authors: | Sakib, Ahmed Shahriar Mukta, Md Saddam Hossain Huda, Fariha Rowshan Islam, AKM Najmul Islam, Tohedul Ali, Mohammed Eunus |
Keywords: | insomnia (56); Twitter (374); word embedding (14); Big 5 personality traits (1); classification (61); social media (1519); prediction model (61); psycholinguistics (2) |
Issue Date: | 9-Dec-2021 |
Publisher: | JMIR Publications |
Citation: | Sakib A, Mukta M, Huda F, Islam A, Islam T, Ali M Identifying Insomnia From Social Media Posts: Psycholinguistic Analyses of User Tweets J Med Internet Res 2021;23(12):e27613 URL: https://www.jmir.org/2021/12/e27613 DOI: 10.2196/27613 |
Series/Report no.: | Vol 23;No 12 |
Abstract: | Many people suffer from insomnia, a sleep disorder characterized by difficulty falling and staying asleep during the night. As social media have become a ubiquitous platform to share users’ thoughts, opinions, activities, and preferences with their friends and acquaintances, the shared content across these platforms can be used to diagnose different health problems, including insomnia. Only a few recent studies have examined the prediction of insomnia from Twitter data, and we found research gaps in predicting insomnia from word usage patterns and correlations between users’ insomnia and their Big 5 personality traits as derived from social media interactions. |
URI: | http://dspace.aiub.edu:8080/jspui/handle/123456789/1673 |
Appears in Collections: | Publications: Journals |
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Dspace.docx | 4.66 MB | Microsoft Word XML | View/Open |
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