Please use this identifier to cite or link to this item: http://dspace.aiub.edu:8080/jspui/handle/123456789/1673
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dc.contributor.authorSakib, Ahmed Shahriar-
dc.contributor.authorMukta, Md Saddam Hossain-
dc.contributor.authorHuda, Fariha Rowshan-
dc.contributor.authorIslam, AKM Najmul-
dc.contributor.authorIslam, Tohedul-
dc.contributor.authorAli, Mohammed Eunus-
dc.date.accessioned2023-11-07T16:25:43Z-
dc.date.available2023-11-07T16:25:43Z-
dc.date.issued2021-12-09-
dc.identifier.citationSakib 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: 10.2196/27613en_US
dc.identifier.urihttp://dspace.aiub.edu:8080/jspui/handle/123456789/1673-
dc.description.abstractMany 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.en_US
dc.language.isoenen_US
dc.publisherJMIR Publicationsen_US
dc.relation.ispartofseriesVol 23;No 12-
dc.subjectinsomnia (56); Twitter (374); word embedding (14); Big 5 personality traits (1); classification (61); social media (1519); prediction model (61); psycholinguistics (2)en_US
dc.titleIdentifying insomnia from social media posts: psycholinguistic analyses of user tweetsen_US
dc.typeThesisen_US
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