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  • Understanding the relationship between perceived and received emotional support in social media

    Rights statement: This is the author’s version of a work that was accepted for publication in Journal of Affective Disorders. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Affective Disorders, 308, 2022 DOI: 10.1016/j.jad.2022.04.105

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Understanding the impact of emotional support on mental health resilience of the community in the social media in Covid-19 pandemic

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Understanding the impact of emotional support on mental health resilience of the community in the social media in Covid-19 pandemic. / Hu, Xuan; Song, Yanqing; Zhu, Ruilin et al.
In: Journal of affective disorders, Vol. 308, 01.07.2022, p. 360-368.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Hu, X, Song, Y, Zhu, R, He, S, Zhou, B, Li, X, Bao, H, Shen, S & Liu, B 2022, 'Understanding the impact of emotional support on mental health resilience of the community in the social media in Covid-19 pandemic', Journal of affective disorders, vol. 308, pp. 360-368. https://doi.org/10.1016/j.jad.2022.04.105

APA

Hu, X., Song, Y., Zhu, R., He, S., Zhou, B., Li, X., Bao, H., Shen, S., & Liu, B. (2022). Understanding the impact of emotional support on mental health resilience of the community in the social media in Covid-19 pandemic. Journal of affective disorders, 308, 360-368. https://doi.org/10.1016/j.jad.2022.04.105

Vancouver

Hu X, Song Y, Zhu R, He S, Zhou B, Li X et al. Understanding the impact of emotional support on mental health resilience of the community in the social media in Covid-19 pandemic. Journal of affective disorders. 2022 Jul 1;308:360-368. Epub 2022 Apr 20. doi: 10.1016/j.jad.2022.04.105

Author

Hu, Xuan ; Song, Yanqing ; Zhu, Ruilin et al. / Understanding the impact of emotional support on mental health resilience of the community in the social media in Covid-19 pandemic. In: Journal of affective disorders. 2022 ; Vol. 308. pp. 360-368.

Bibtex

@article{06b9785fa6074ad785e535ce9b4a9c49,
title = "Understanding the impact of emotional support on mental health resilience of the community in the social media in Covid-19 pandemic",
abstract = "Emotional support in social media can act as a buffer against the negative impact of affective disorders. However, empirical evidence relating to emotional support in social media and how it influences the wider public remains scanty. The objective of this study is therefore to conduct a prototype investigation into the translation mechanism of emotional support in social media, providing empirical evidence for practitioners to use to tackle mental health issues for the wider public. A regression model is proposed to examine the relationship between perceived and received emotional support. Received emotional support is set as the dependent variable and measured using public activity. Perceived emotional support is derived using Natural Language Processing (NLP)-based content analysis. The model is then analyzed using a panel date with a total number of 61,297 posts from 17 Weibo accounts in 17 provincial administrative units in China. The relationship between perceived and received emotional support is not linear but complex, suggesting that translation of emotional support is not automatic. Further, our empirical evidence suggests that the translation of emotional support in social media is affected by frequency and pandemic stage. The study does not examine the direct relationship between perceived and received emotional support, instead adopting public activity as a proxy for the latter construct. In addition, the relationship between perceived and received emotional support is more complex than linear, requiring further model and theory development. [Abstract copyright: Copyright {\textcopyright} 2022 Elsevier B.V. All rights reserved.]",
keywords = "Affective disorders, Perceived emotional support, COVID-19, Received emotional support, Social media",
author = "Xuan Hu and Yanqing Song and Ruilin Zhu and Shuang He and Bowen Zhou and Xuelian Li and Han Bao and Shan Shen and Bingsheng Liu",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Journal of Affective Disorders. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Affective Disorders, 308, 2022 DOI: 10.1016/j.jad.2022.04.105",
year = "2022",
month = jul,
day = "1",
doi = "10.1016/j.jad.2022.04.105",
language = "English",
volume = "308",
pages = "360--368",
journal = "Journal of affective disorders",
issn = "1573-2517",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Understanding the impact of emotional support on mental health resilience of the community in the social media in Covid-19 pandemic

AU - Hu, Xuan

AU - Song, Yanqing

AU - Zhu, Ruilin

AU - He, Shuang

AU - Zhou, Bowen

AU - Li, Xuelian

AU - Bao, Han

AU - Shen, Shan

AU - Liu, Bingsheng

N1 - This is the author’s version of a work that was accepted for publication in Journal of Affective Disorders. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Affective Disorders, 308, 2022 DOI: 10.1016/j.jad.2022.04.105

PY - 2022/7/1

Y1 - 2022/7/1

N2 - Emotional support in social media can act as a buffer against the negative impact of affective disorders. However, empirical evidence relating to emotional support in social media and how it influences the wider public remains scanty. The objective of this study is therefore to conduct a prototype investigation into the translation mechanism of emotional support in social media, providing empirical evidence for practitioners to use to tackle mental health issues for the wider public. A regression model is proposed to examine the relationship between perceived and received emotional support. Received emotional support is set as the dependent variable and measured using public activity. Perceived emotional support is derived using Natural Language Processing (NLP)-based content analysis. The model is then analyzed using a panel date with a total number of 61,297 posts from 17 Weibo accounts in 17 provincial administrative units in China. The relationship between perceived and received emotional support is not linear but complex, suggesting that translation of emotional support is not automatic. Further, our empirical evidence suggests that the translation of emotional support in social media is affected by frequency and pandemic stage. The study does not examine the direct relationship between perceived and received emotional support, instead adopting public activity as a proxy for the latter construct. In addition, the relationship between perceived and received emotional support is more complex than linear, requiring further model and theory development. [Abstract copyright: Copyright © 2022 Elsevier B.V. All rights reserved.]

AB - Emotional support in social media can act as a buffer against the negative impact of affective disorders. However, empirical evidence relating to emotional support in social media and how it influences the wider public remains scanty. The objective of this study is therefore to conduct a prototype investigation into the translation mechanism of emotional support in social media, providing empirical evidence for practitioners to use to tackle mental health issues for the wider public. A regression model is proposed to examine the relationship between perceived and received emotional support. Received emotional support is set as the dependent variable and measured using public activity. Perceived emotional support is derived using Natural Language Processing (NLP)-based content analysis. The model is then analyzed using a panel date with a total number of 61,297 posts from 17 Weibo accounts in 17 provincial administrative units in China. The relationship between perceived and received emotional support is not linear but complex, suggesting that translation of emotional support is not automatic. Further, our empirical evidence suggests that the translation of emotional support in social media is affected by frequency and pandemic stage. The study does not examine the direct relationship between perceived and received emotional support, instead adopting public activity as a proxy for the latter construct. In addition, the relationship between perceived and received emotional support is more complex than linear, requiring further model and theory development. [Abstract copyright: Copyright © 2022 Elsevier B.V. All rights reserved.]

KW - Affective disorders

KW - Perceived emotional support

KW - COVID-19

KW - Received emotional support

KW - Social media

U2 - 10.1016/j.jad.2022.04.105

DO - 10.1016/j.jad.2022.04.105

M3 - Journal article

C2 - 35460730

VL - 308

SP - 360

EP - 368

JO - Journal of affective disorders

JF - Journal of affective disorders

SN - 1573-2517

ER -