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Competitive peer influence on knowledge contribution behaviors in online Q&A communities: a social comparison perspective

独创性 人气 感知 线程(计算) 心理学 多级模型 社会心理学 加权 计算机科学 创造力 医学 操作系统 机器学习 放射科 神经科学
作者
Chencheng Shi,Ping Hu,Weiguo Fan,Liangfei Qiu
出处
期刊:Internet Research [Emerald (MCB UP)]
被引量:1
标识
DOI:10.1108/intr-07-2022-0510
摘要

Purpose Users' knowledge contribution behaviors are critical for online Q&A communities to thrive. Well-organized question threads in online Q&A communities enable users to clearly read existing answers and their evaluations before contributing. Based on the social comparison and peer influence literature, the authors examine peer influence on the informativeness of knowledge contributions in competitive settings. The authors also consider three levels of moderating factors concerning individuals' perception of competitiveness: question level, thread level and contributor level. Design/methodology/approach The authors collected data from one of the largest online Q&A communities in China. The hypotheses were validated using hierarchical linear models with cross-classified random effects. The generalized propensity score weighting method was employed for the robustness check. Findings The authors demonstrate the peer influence due to social comparison concerns among knowledge contribution behaviors in the same question thread. If more prior knowledge contributors choose to contribute long answers in the question thread, the subsequent contributions are more informative. This peer influence is stronger for factual questions and questions with higher popularity of answering but weaker in recommendation-type and well-answered questions and for contributors with higher social status. Originality/value This research provides a new cue of peer influence on online UGC contributions in competitive settings initiated by social comparison concerns. Additionally, the authors identify three levels of moderating factors (question level, thread level and contributor level) that are specific to online Q&A settings and are related to a contributor's perception of competitiveness, which affect the direct effect of peer influence on knowledge contributions. Rather than focus on motivation and quality evaluation, the authors concentrate on the specific content of online knowledge contributions. Peer influence here is not based on an actual acquaintance or a following relationship but on answering the same question. The authors also illustrate the competitive peer influence in subjective and personalized behaviors in online UGC communities.
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