Patterns in negative emotions, sleep disorders, and temperature: Evidence from microblog big data
Existing studies have shown that temperature is related to mental illness and sleep disorders. However, few studies have explored the relationship between temperature and microblog negative emotions (MNE) and the predictive effect of MNE on sleep disorders. The present study elucidating the temperat...
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Format: | Article |
Language: | English |
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Elsevier
2023-11-01
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Series: | Heliyon |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023091958 |
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author | Xiaowen Li Jun Zhang Bing Li |
author_facet | Xiaowen Li Jun Zhang Bing Li |
author_sort | Xiaowen Li |
collection | DOAJ |
description | Existing studies have shown that temperature is related to mental illness and sleep disorders. However, few studies have explored the relationship between temperature and microblog negative emotions (MNE) and the predictive effect of MNE on sleep disorders. The present study elucidating the temperature patterns of MNE and sleep disorders, examines the predictive capability of these adverse emotions in precipitating sleep disorders, and operating within the schema of “climate-psychology-behavior”. A negative binomial regression model (NBR) was formulated, amalgamating Temperature data, negative affective information procured from microblog, and sleep disorder records. Temperature and Apparent Air Temperature (AAT) were found to have a non-linear association with microblog negative emotions and sleep disorders, exhibiting a modest effect within a specified range, while extreme temperatures (both high and low) demonstrated substantial effects. In the constructed model, gender serves as a moderating factor, with females being more susceptible to temperature and AAT effects on MNE and sleep disorders than their male counterparts. Interestingly, AAT surfaced as a superior predictor compared to actual temperature. MNE were effective predictors of sleep disorders. Employing social media-centric models, as showcased in this study, augments the identification and prevention strategies targeting disease symptoms or pathologies within mental and public health domains. |
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id | doaj.art-2b915b63be504ccb8010114e2097f294 |
institution | Directory Open Access Journal |
issn | 2405-8440 |
language | English |
last_indexed | 2024-03-09T09:17:33Z |
publishDate | 2023-11-01 |
publisher | Elsevier |
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series | Heliyon |
spelling | doaj.art-2b915b63be504ccb8010114e2097f2942023-12-02T07:04:51ZengElsevierHeliyon2405-84402023-11-01911e21987Patterns in negative emotions, sleep disorders, and temperature: Evidence from microblog big dataXiaowen Li0Jun Zhang1Bing Li2College of Geography and Tourism, Anhui Normal University, Wuhu, 241000, China; Department of Psychology, Chosun University, Gwangju, 61452, South Korea; Corresponding author. College of Geography and Tourism, Anhui Normal University, Wuhu, 241000, China.Department of Psychology, Chosun University, Gwangju, 61452, South KoreaCollege of Art Design & Physical Education, Chosun University, Gwangju, 61452, South KoreaExisting studies have shown that temperature is related to mental illness and sleep disorders. However, few studies have explored the relationship between temperature and microblog negative emotions (MNE) and the predictive effect of MNE on sleep disorders. The present study elucidating the temperature patterns of MNE and sleep disorders, examines the predictive capability of these adverse emotions in precipitating sleep disorders, and operating within the schema of “climate-psychology-behavior”. A negative binomial regression model (NBR) was formulated, amalgamating Temperature data, negative affective information procured from microblog, and sleep disorder records. Temperature and Apparent Air Temperature (AAT) were found to have a non-linear association with microblog negative emotions and sleep disorders, exhibiting a modest effect within a specified range, while extreme temperatures (both high and low) demonstrated substantial effects. In the constructed model, gender serves as a moderating factor, with females being more susceptible to temperature and AAT effects on MNE and sleep disorders than their male counterparts. Interestingly, AAT surfaced as a superior predictor compared to actual temperature. MNE were effective predictors of sleep disorders. Employing social media-centric models, as showcased in this study, augments the identification and prevention strategies targeting disease symptoms or pathologies within mental and public health domains.http://www.sciencedirect.com/science/article/pii/S2405844023091958Microblog big dataApparent air temperatureNatural language processing implementationEmotion identification techniquesNegative binomial regression modeling |
spellingShingle | Xiaowen Li Jun Zhang Bing Li Patterns in negative emotions, sleep disorders, and temperature: Evidence from microblog big data Heliyon Microblog big data Apparent air temperature Natural language processing implementation Emotion identification techniques Negative binomial regression modeling |
title | Patterns in negative emotions, sleep disorders, and temperature: Evidence from microblog big data |
title_full | Patterns in negative emotions, sleep disorders, and temperature: Evidence from microblog big data |
title_fullStr | Patterns in negative emotions, sleep disorders, and temperature: Evidence from microblog big data |
title_full_unstemmed | Patterns in negative emotions, sleep disorders, and temperature: Evidence from microblog big data |
title_short | Patterns in negative emotions, sleep disorders, and temperature: Evidence from microblog big data |
title_sort | patterns in negative emotions sleep disorders and temperature evidence from microblog big data |
topic | Microblog big data Apparent air temperature Natural language processing implementation Emotion identification techniques Negative binomial regression modeling |
url | http://www.sciencedirect.com/science/article/pii/S2405844023091958 |
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