I Know You: User Profiling on Social Media Usage of Chinese Private University Students

IF 0.5 Q3 SOCIAL SCIENCES, INTERDISCIPLINARY Jurnal Ilmiah Peuradeun Pub Date : 2024-01-30 DOI:10.26811/peuradeun.v12i1.1076
Yunyan Wang, Poh-Chuin Teo
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Abstract

Chinese university students’ use of social media is becoming increasingly diverse, and students from private universities in China have different group characteristics than those from public universities. This research endeavoured to establish a comprehensive user profile of Chinese private university students by examining their social media usage patterns. The purpose was to gain profound insights into the distinctive attributes of students in China’s private universities within the context of the current era characterised by extensive data availability. This study employed a questionnaire-based research approach to acquire a dataset consisting of 673 instances of social media usage among students enrolled in private universities in China. Subsequently, exploratory factor analysis was performed using the Statistical Package for Social Sciences (SPSS) software, extracting five (5) categorical feature tags. Combined with the extracted feature tags and the usage status and perception dimension data, the K-means cluster analysis method was used to perform rapid clustering to derive four (4) differentiated groups comprising information exchange-oriented users, instrument-oriented users, dependent-oriented users and entertainment-oriented users. Furthermore, thorough analysis and description of the essential attributes for these 4 user profile categories have been conducted by incorporating the fundamental user information.
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我认识你中国私立大学学生社交媒体使用情况的用户特征分析
中国大学生对社交媒体的使用日益多样化,中国民办高校的学生与公立大学的学生有着不同的群体特征。本研究试图通过考察中国民办高校学生的社交媒体使用模式,建立一个全面的中国民办高校学生用户画像。目的是在当前数据广泛可用的时代背景下,深入了解中国民办高校学生的独特属性。本研究采用问卷调查的研究方法,获取了中国民办高校学生使用社交媒体的 673 次数据集。随后,利用社会科学统计软件包(SPSS)进行了探索性因素分析,提取了五(5)个分类特征标签。结合提取的特征标签、使用状况和感知维度数据,采用 K-means 聚类分析方法进行快速聚类,得出信息交换型用户、工具型用户、依赖型用户和娱乐型用户四个差异化群体。此外,还结合用户的基本信息,对这 4 类用户的基本属性进行了深入分析和描述。
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来源期刊
Jurnal Ilmiah Peuradeun
Jurnal Ilmiah Peuradeun SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
1.00
自引率
80.00%
发文量
50
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