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A dual-process model to explain self-disclosure on online social networking sites: examining the moderating effect of enjoyment

Shanshan Zhang (School of Management, Zhejiang University of Technology, Hangzhou, China)
Fengchun Huang (School of Management, Zhejiang University of Technology, Hangzhou, China)
Lingling Yu (School of Management, Shanghai University, Shanghai, China)
Jeremy Fei Wang (Pamplin College of Business, Virginia Tech, Blacksburg, Virginia, USA)
Paul Benjamin Lowry (Pamplin College of Business, Virginia Tech, Blacksburg, Virginia, USA)

Internet Research

ISSN: 1066-2243

Article publication date: 28 November 2023

Issue publication date: 19 July 2024

602

Abstract

Purpose

Researchers continue to address the concept of self-disclosure because it is foundational for helping social networking sites (SNS) function and thrive. Nevertheless, the authors' literature review indicates that uncertainty remains around the underlying mechanisms and factors involved in the self-disclosure process. The purpose of this research is to better understand the self-disclosure process from the lens of dual-process theory (DPT). The authors consider both the controlled factors (i.e. self-presentation and reciprocity) and an automatic factor (i.e. social influence to use an SNS) involved in self-disclosure and broaden The authors proposed a model to include the interactive facets of enjoyment.

Design/methodology/approach

The proposed model was empirically validated by conducting a survey among users of WeChat Moments in China.

Findings

As hypothesized, this research confirms that enjoyment and automatic processing (i.e. social influence to use an SNS) are complementary in the SNS self-disclosure process and enjoyment negatively moderates the positive relationship between controlled factor (i.e. self-presentation) and self-disclosure.

Originality/value

Theoretically, this study offers a new perspective on explaining SNS self-disclosure by adopting DPT. Specifically, this study contributes to the extant SNS research by applying DPT to examine how the controlled factors and the automatic factor shape self-disclosure processes and how enjoyment influences vary across these processes – enriching knowledge about SNS self-disclosure behaviors. Practically, the authors provide important design guidelines to practitioners concerning devising mechanisms to foster more automatic-enjoyable value-added functions to improve SNS users' participation and engagement.

Keywords

Acknowledgements

The authors express their gratitude for the developmental critical comments and patience of the editors, the reviewers, and the Internet Research Editorial Office. The authors also thank Jingzhi Zhang, Tao Liu, Jia Liu, Ron Chi-Wai Kwok, Suqin Liao, Lei Zhao, Ken Cheng, Yuting Zhang, Jing Wang, and other friends and colleagues for their kind support and help. This research was supported by the Ministry of Education of Humanities and Social Science Youth Project in China [Grant No. 22YJC630206], the Zhejiang Provincial Natural Science Foundation of China [Grant No. LQ23G020008], the Program for National Social Science Foundation of China [Grant No. 23CGL075], the Shanghai University Sailing Program, and the National Natural Science Foundation of China [Grant No.72002203].

Since submission of this article, the following author(s) have updated their affiliation(s): Jeremy Fei Wang is at the Flagler College, Saint Augustine, Florida, USA.

Citation

Zhang, S., Huang, F., Yu, L., Wang, J.F. and Lowry, P.B. (2024), "A dual-process model to explain self-disclosure on online social networking sites: examining the moderating effect of enjoyment", Internet Research, Vol. 34 No. 4, pp. 1456-1487. https://doi.org/10.1108/INTR-08-2021-0545

Publisher

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Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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