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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

    Accepted author manuscript, 1.11 MB, PDF document

    Embargo ends: 20/04/23

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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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

E-pub ahead of print
  • Xuan Hu
  • Yanqing Song
  • Ruilin Zhu
  • Shuang He
  • Bowen Zhou
  • Xuelian Li
  • Han Bao
  • Shan Shen
  • Bingsheng Liu
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<mark>Journal publication date</mark>1/07/2022
<mark>Journal</mark>Journal of affective disorders
Volume308
Number of pages9
Pages (from-to)360-368
Publication StatusE-pub ahead of print
Early online date20/04/22
<mark>Original language</mark>English

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 © 2022 Elsevier B.V. All rights reserved.]

Bibliographic note

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