Investigating the Impact of Social Media on Driving Safety: A Case Study in Hong Kong

2025-99-0254

12/23/2025

Authors
Abstract
Content
Focusing on drivers in Hong Kong, this paper analyzes how social media usage contributes to inattentive driving and the associated safety consequences. Data were collected using a questionnaire-based survey and analyzed through chi-square tests, Fisher’s exact tests, and Cramér’s V effect size calculations to examine the relationships between demographic and driving-related factors—including gender, age group, education level, driving experience, and self-rated driving skills—and the level of high-risk perception. The findings reveal that gender, age, experience, and Self-assessed driving ability significantly influence drivers’ perception of high-risk situations. Furthermore, significant interaction effects were observed among these variables, indicating that they do not operate in isolation but rather interact to shape risk perception. For example, middle-aged and older female drivers with higher education levels and extensive driving experience demonstrated a heightened perception of high-risk scenarios, while increased driving experience was associated with improved high-risk perception among younger drivers. This study provides a systematic statistical analysis of how social media usage habits influence risk perception across different demographic groups, offering a theoretical foundation for the development of targeted safety interventions for high-risk populations. The results underscore the significance of accounting for the interaction between demographic and driving-related factors in designing effective strategies to mitigate distracted driving and enhance road safety.
Meta TagsDetails
Pages
8
Citation
Dong, Jinhai, Haocheng Ye, Ziheng Cui, and Yang Chen, "Investigating the Impact of Social Media on Driving Safety: A Case Study in Hong Kong," SAE Technical Paper 2025-99-0254, 2025-, .
Additional Details
Publisher
Published
Dec 23
Product Code
2025-99-0254
Content Type
Technical Paper
Language
English