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Exploring the relationship between social presence and learners’ prestige in MOOC discussion forums using automated content analysis and social network analysis

声望 心理学 感恩 社会化媒体 社交网络(社会语言学) 社会心理学 社会网络分析 万维网 计算机科学 语言学 哲学
作者
Wenting Zou,Xiao Hu,Zilong Pan,Chenglu Li,Ying Cai,Min Liu
出处
期刊:Computers in Human Behavior [Elsevier BV]
卷期号:115: 106582-106582 被引量:132
标识
DOI:10.1016/j.chb.2020.106582
摘要

Research has repeatedly proven the importance of social interactions in online learning contexts such as Massive Open Online Courses (MOOCs), where learners often reported isolation and a lack of peer support. Previous studies of social presence suggested that the ways learners present themselves socially online affect their learning outcomes. In order to further understand the role of learners' social presence, this study attempts to examine the relationship between social presence and learners' prestige in the learner network of a MOOC. An automated text classification model based on the latest machine learning techniques was developed to identify different social presence indicators from forum posts, while two metrics (in-degree and authority score) in social network analysis (SNA) were used to measure learners' prestige in the learner network. Results revealed that certain social presence indicators such as Asking questions, Expressing gratitude, Self-disclosure, Sharing resources and Using Vocatives have positive correlations with learners' prestige, while the expressions of Disagreement/doubts/criticism and Negative emotions were counterproductive to learners' prestige. The findings not only reinforce the importance of social presence in online learning, but also shed light on the strategies of leveraging social presence to improve individual's prestige in social learning contexts like MOOCs.
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