Information overload and the intention to reduce SNS usage: the mediating roles of negative social comparison and fatigue-Reference-Cited by-同舟云学术

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Information overload and the intention to reduce SNS usage: the mediating roles of negative social comparison and fatigue

Published:2020-08-31 Issue: Volume: Page:
ISSN:1046-1310
Container-title:Current Psychology
language:en
Short-container-title:Curr Psychol

Author:

Niu Gengfeng,Yao Liangshuang,Tian Yuan,Sun Xiaojun,Zhou Zongkui

Funder

Ministry of Education Projects of Philosophy and Social Sciences Research

National Natural Science Foundation of China

the Soft Science Research Project of Shaanxi Province

the Research Program Funds of the Collaborative Innovation Center of Assessment toward Basic Education Quality

Publisher

Springer Science and Business Media LLC

Subject

General Psychology

Link

https://link.springer.com/content/pdf/10.1007/s12144-020-01043-1.pdf

Reference40 articles.

1. Appel, H., Gerlach, A. L., & Crusius, J. (2016). The interplay between Facebook use, social comparison, envy, and depression. Current Opinion in Psychology, 9, 44–49. https://doi.org/10.1016/j.copsyc.2015.10.006.

2. Brandenberg, G., Ozimek, P., Bierhoff, H. W., & Janker, C. (2018). The relation between use intensity of private and professional SNS, social comparison, self-esteem, and depressive tendencies in the light of self-regulation. Behaviour & Information Technology, 38(6), 578–591. https://doi.org/10.1080/0144929X.2018.1545049.

3. Bright, L. F., Kleiser, S. B., & Grau, S. L. (2015). Too much Facebook? An exploratory examination of social media fatigue. Computers in Human Behavior, 44, 148–155. https://doi.org/10.1016/j.chb.2014.11.048.

4. Cao, X., & Sun, J. (2018). Exploring the effect of overload on the discontinuous intention of social media users: An S-O-R perspective. Computers in Human Behavior, 81, 10–18. https://doi.org/10.1016/j.chb.2017.11.035.

5. Cheung, R., & Vogel, D. (2013). Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. Computers & Education, 63(2), 160–175. https://doi.org/10.1016/j.compedu.2012.12.003.

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