情报科学

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基于产品评论挖掘的消费者偏好分析

  

  1. 安徽大学管理学院

User preference analysis based on product review mining

摘要:

[目的/意义]消费者评论数量巨大且充满随意性,因此需要对评论信息进行分析,信息分析可以给潜在的消费者选购相应产品时提供有价值参考,可以给商家提供消费者对产品的反馈意见,也可以给平台改善服务提供参考,从而实现消费者、商家和平台的共赢。[方法/过程]通过对电商平台的产品评论进行分析,挖掘出产品特点和消费者情感倾向,以从京东商城爬取的部分产品评论文本为研究对象,使用词频、词云分析的方法对评论中的产品特征进行抽取,分析消费者对产品属性的偏好,通过情感倾向计算方法,对五种不同类别的产品评论进行情感倾向分析,并研究消费者对产品属性的偏好和情感倾向间的关系。[结果/结论]研究结果表明,对于不同类型的产品,消费者有不同的属性偏好,而且消费者关注的产品特征数量也不同。在此基础上,分别对商家、电商平台和消费者提出了有针对性的建议。

关键词:

消费者评论, 评论挖掘, 产品特点, 情感分析

Abstract:

[Purpose/significance]The number of consumer reviews is huge and full of randomness, so it is necessary to analyze the review information. Information analysis can provide valuable reference for potential consumers when purchasing corresponding products, can provide consumers' feedback on products to businesses, and can also provide reference for the platform to improve services, so as to achieve a win-win situation among consumers, businesses and the platform.[Method/process]Through the analysis of product reviews on e-commerce platform, the characteristics of goods and users' emotional tendency are mined out. Taking some product reviews texts crawled from Jingdong Mall as the research object, the article extracts the commodity features in the reviews by using the method of word frequency and word cloud analysis, and analyzes the emotional tendency of five different types of commodity reviews through the calculation method of sentiment tendency.[Result/conclusion]The results show that for different types of goods, consumers have different attribute preferences, and the number of product features that users pay attention to is also different. On this basis, targeted suggestions are put forward for businesses, e-commerce platforms and consumers.

Key words:

User review, comment mining, commodity characteristics, sentiment analysis