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Related Experiment Video

Updated: Jun 12, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

SNSs usage among Chinese internet users: an empirical study.

Junqi Shi¹, Qikun Niu

¹Department of Psychology, Peking University, Beijing, China. jungqi_shi@pku.edu.cn

Studies in Health Technology and Informatics

|June 15, 2010

Summary

This study reveals how Chinese social network site (SNS) usage is influenced by perceived ease of use and usefulness, with internet self-efficacy playing an indirect role. These findings help describe and predict user behavior on platforms like Renren and Kaixin.

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Last Updated: Jun 12, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

Area of Science:

Social Sciences
Information Science
Human-Computer Interaction

Background:

Social Network Sites (SNSs) are popular globally, with Renren and Kaixin being dominant platforms in China.
Limited research exists on the specific factors influencing SNS usage within the Chinese context.

Purpose of the Study:

To investigate the key variables affecting Chinese SNS usage.
To apply the Technology Acceptance Model (TAM) to understand user behavior on Chinese SNSs.

Main Methods:

A survey was conducted with 777 Chinese participants.
Structural Equation Modeling (SEM) was employed to analyze the data.

Main Results:

Perceived ease of use positively impacts perceived usefulness.
Perceived usefulness significantly influences SNS use intensity.
Internet self-efficacy indirectly affects SNS use intensity by influencing perceived ease of use.

Conclusions:

The study validates the TAM framework for predicting Chinese SNS usage.
Findings provide insights into the drivers of engagement with social network sites in China.
The results can inform strategies for platform design and user engagement.