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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

The relationship among short-form video addiction, self-control, and emotional symptoms in college students: a

Yani Zhang¹, Qingyuan Yu¹, Tao Li²

¹Key Laboratory of Basic Research and Health Management on Chronic Diseases in Heilongjiang Province, Harbin Medical University Daqing Campus, 39 Xinyang Road, Daqing City, Heilongjiang Province, 163319, China.

BMC Public Health

|February 3, 2026

Abstract

Background:

Traditional regression or structural equation modeling often falls short in revealing the complex dynamic interactions among multiple variables. In contrast, network analysis not only conceptualizes college students'short video addiction, self-control, and emotional symptoms as interacting nodes, but also visually uncovers core symptoms and bridging mechanisms that are elusive to conventional approaches. Employing this method, the present study aims to elucidate the interactive mechanisms among college students' short video addiction, self-control, and emotional symptoms, thereby providing finer-grained empirical evidence for developing targeted intervention strategies.

Objective:

This study employs network analysis to explore the relationships among short video addiction, self-control, and emotional symptoms in college students, aiming to provide empirical evidence for developing targeted interventions.

Methods:

A cross-sectional design was adopted, with convenience sampling used to recruit participants from a medical university. A total of 5,754 valid questionnaires were collected. Measurement tools included the Short Video Addiction Scale for College Students, the Brief Self-Control Scale, the Self-Rating Depression Scale (SDS), and the Self-Rating Anxiety Scale (SAS). Regularized partial correlation networks were constructed using the "qgraph" and "bootnet" packages in R, and node centrality along with network stability were evaluated.

Results:

The study revealed a complex interactive structure among short video addiction, self-control, and emotional symptoms. Statistically, "Uncontrollability" within short video addiction and "Self-discipline" within self-control demonstrated high centrality.

Conclusion:

The study reveals a complex interactive structure among short video addiction, self-control, and emotional symptoms. Statistically, "Uncontrollability" within short video addiction and "Self-discipline" within self-control demonstrated high centrality. In practical terms, the findings suggest that enhancing self-discipline may serve as an effective entry point for intervening in addictive short video use behaviors.

Keywords:

College students Emotional symptoms Network analysis Self-control Short video addiction

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