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Understanding user behavior in online feedback reporting

机译:了解在线反馈报告中的用户行为

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Online reviews have become increasingly popular as a way to judge the quality of various products and services. Previous work has demonstrated that contradictory reporting and underlying user biases make judging the true worth of a service difficult. In this paper, we investigate underlying factors that influence user behavior when reporting feedback. We look at two sources of information besides numerical ratings: linguistic evidence from the textual comment accompanying a review, and patterns in the time sequence of reports. We first show that groups of users who amply discuss a certain feature are more likely to agree on a common rating for that feature. Second, we show that a user's rating partly reflects the difference between true quality and prior expectation of quality as inferred from previous reviews. Both give us a less noisy way to produce rating estimates and reveal the reasons behind user bias.Our hypotheses were validated by statistical evidence from hotel reviews on the TripAdvisor website.>>> af++ US8909771B2 . 2014-12-09

机译:用于为消费者反馈社交媒体分析平台使用全球位置信息,2D和3D映射,社交媒体以及用户行为和信息的系统和方法,用于为过去,现在或未来的全球品牌产品或服务提供在线消费者反馈的分析测量数据未来的客户,用户和/或目标市场

  • 机译:用于将全球位置信息,2D和3D映射,社交媒体以及用户行为和信息用于消费者反馈社交媒体分析平台的系统和方法,用于为全球品牌产品或服务提供在线消费者反馈的分析测量数据或未来的客户,用户或目标市场

  • 机译:用于确定在线行为对离线销售的影响的动态地理位置参数,可以获取与产品相关的用户的在线行为

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