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<p>Given the information overload brought about by the widespread application of e-commerce questions and answers (Q&amp;A), it has become necessary to identify valuable Q&amp;As in a sea of Q&amp;As. This study is the first to introduce the concept of popularity in e-commerce Q&amp;As to distinguish the value of Q&amp;As, and construct an effect framework for the impact of popular Q&amp;A on subsequent reviews based on signal theory and expectation disconfirmation theory to prove the rationality of this identification method. We collect data from the JD.com and propose the information and confirmation effects of popular Q&amp;A. Through deep learning and rule-based methods, the mediating variables of the explanation mechanism are constructed. Firstly, we analyse the most popular Q&amp;A and the results show that for different product type, (1) the information effect of the most popular Q&amp;A reduces subsequent negative reviews related to product quality (<i>search products</i>) and product fit (<i>experience products</i>), leading to an increase in ratings; (2) the confirmation effect of the most popular Q&amp;A reduces the content about product quality (<i>search products</i>) and product fit (<i>experience products</i>) in reviews, leading to a decrease in review length. Secondly, this study further proposes reference thresholds for identifying what is a popular Q&amp;A. Finally, we repeat the above analysis for other less popular Q&amp;As to verify the effectiveness of the identification method. The results provide practical guidance for identifying the value of Q&amp;As.</p>

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The Value of Popular Q&As in E-commerce Platform: The Different Effects by Products Type

  • 期刊论文

  • 发表日期：

    2026年7月17日

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  • Yurong Zhang,
  • Qingping Zhao

摘要

Given the information overload brought about by the widespread application of e-commerce questions and answers (Q&A), it has become necessary to identify valuable Q&As in a sea of Q&As. This study is the first to introduce the concept of popularity in e-commerce Q&As to distinguish the value of Q&As, and construct an effect framework for the impact of popular Q&A on subsequent reviews based on signal theory and expectation disconfirmation theory to prove the rationality of this identification method. We collect data from the JD.com and propose the information and confirmation effects of popular Q&A. Through deep learning and rule-based methods, the mediating variables of the explanation mechanism are constructed. Firstly, we analyse the most popular Q&A and the results show that for different product type, (1) the information effect of the most popular Q&A reduces subsequent negative reviews related to product quality (search products) and product fit (experience products), leading to an increase in ratings; (2) the confirmation effect of the most popular Q&A reduces the content about product quality (search products) and product fit (experience products) in reviews, leading to a decrease in review length. Secondly, this study further proposes reference thresholds for identifying what is a popular Q&A. Finally, we repeat the above analysis for other less popular Q&As to verify the effectiveness of the identification method. The results provide practical guidance for identifying the value of Q&As.