Does the review deserve more helpfulness when its title resembles the content? Locating helpful reviews by text mining
作者: Yusheng zhouShuiqing Yangyixiao liYuangao chenJianrong YaoAtika Qazi
作者单位: 1School of information management and Engineering, Zhejiang University of Finance and Economics, China
2Centre for Lifelong Learning, University of Brunei Darussalam, Gadong BE1410, Brunei
刊名: Information Processing and Management, 2020, Vol.57 (2)
来源数据库: Elsevier Journal
DOI: 10.1016/j.ipm.2019.102179
关键词: Online reviewsReview helpfulnessText miningReview titleSimilaritySentiment analysis
原始语种摘要: Abstract(#br)Online review helpfulness has always sparked a heated discussion among academics and practitioners. Despite the fact that research has extensively examined the impacts of review title and content on perceptions of online review helpfulness, the underlying mechanism of how the similarities between a review' title and content may affect review helpfulness has been rarely explored. Based on mere exposure theory, a research model reflecting the influences of title-content similarity and sentiment consistency on review helpfulness was developed and empirically examined by using data collected from 127,547 product reviews on Amazon.com. The TF-IDF and the cosine of similarity were used for measuring the text similarity between review title and review content, and the Tobit model...
全文获取路径: Elsevier  (合作)
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影响因子:0.817 (2012)

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关键词翻译
关键词翻译
  • review 复审
  • title 标题
  • content 品位
  • sentiment 感情
  • similarity 相似性
  • Tobit 托比特书
  • more 更多
  • mining 矿业
  • helpful 有益的
  • research