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Analysis about the Text Content's Effect on the Usefulness of Online Comments based on Search Type Products

机译：根据搜索类型产品分析文本内容对在线评论有用性的影响

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This article aims at the Amazon comments data for the original object, the processed data as direct object, using SPSS data analysis tool to study the content of online comments about what factors will affect the online comments usefulness of search type products, and thus improve the theories about influence factors of usefulness of online comments. The study found that extreme comment star, products with high scoring and appearance of sigh emotion are significantly positively correlated with the usefulness of online comments, but large rate variance is negatively correlated with the usefulness of online comments. These conclusions can not only provide the Amazon with recommendations to improve the online comment system to improve their competitive advantage, but also provide suggestions for consumers to have a positive and effective buying behavior.
机译：本文的目标是原始对象的亚马逊评论数据，将处理数据作为直接对象，使用SPSS数据分析工具研究在线评论的内容有关什么因素会影响搜索类型产品的有用性，从而改善 关于在线评论有用性的影响因素的理论。 该研究发现，极端的评论明星，叹息和外观的叹息和外观的产品与在线评论的有用性显着相关，但大的速率方差与在线评论的有用性负相关。 这些结论不仅可以向亚马逊提供改进在线评论系统以提高其竞争优势的建议，而且还为消费者提供积极和有效的购买行为提供建议。

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