评价理论视角下分析中国消费者网购评论

发布时间：2018-04-25 09:33

本文选题：中国消费者网购评论 + 评价理论　；参考：《东北师范大学》2017年硕士论文

【摘要】：近些年随着电子商务的发展和网络用户的增加,消费模式也有了一定程度的变化。越来越多的消费者选择网购。因此,能够给潜在消费者提供另一方面的参考信息的网购评论也逐渐成为热门话题。消费者通过撰写评论对商品和商家服务做出反馈,以表明自己的态度并试图对潜在消费者的决定产生影响。虽然越来越多的国内外学者已经对网购评论进行各个方面的研究,但是几乎没有人以中国网购评论为语料。所以从评价理论视角对中国网购评论进行研究是很有意义的。本文从淘宝网选取了900条中国网购评论作为语料。采用定量和定性结合的研究方法进行分析。利用定量分析计算了各种评价资源出现的频率和分布情况。采用定性的方法分析了统计结果所体现的意义。本文主要研究三个问题:(1)不同的评价资源的实现形式是什么?不同的评价资源在中国网购评论中出现的频率是什么?(2)不同的评价资源在好评中评差评的分布情况是怎么样的?(3)中国网购评论是如何通过评价资源实现人际意义的?通过数据分析,研究发现不同的评价资源是通过如“喜欢”,“值得”,“果然”,“我认为”,“少”,“有点”等等词语体现的。经过统计表明在所选取的例子中共有5740个评价资源。其中,表示态度的最多,总计3784。其次是级差资源,共1137个,占所有评价资源的24%,最少的是介入资源,共549个,占所有评价资源的10%。第二,好评中所包含的评价资源最多,总计2163个。其次是差评,共1720个评价资源。中评中所包含的评价资源最少,共计1587个。三种评价中所包含的态度资源最多,其次是级差资源,介入资源最少。第三,网购评论可以实现人际意义。消费者利用态度资源表达他们的态度,从而说服潜在消费者购买商品或放弃购买的想法。消费者利用介入资源表明立场,并与潜在消费者建立友好的关系,以实现劝说的目的。同时他们利用极差资源与潜在消费者结盟,同时让他们对商品商家和其他方面有一个更为清晰地了解。本文弥补了中国消费者网购评论研究的不足,并且对评价理论视角下的中国消费者网购评论研究方向提出了建议。
[Abstract]:In recent years, with the development of e-commerce and the increase of network users, consumption patterns have changed to a certain extent. More and more consumers choose to buy online. Therefore, online shopping reviews, which can provide other reference information to potential consumers, have gradually become a hot topic. Consumers use comments to give feedback on goods and business services to show their attitude and try to influence potential consumers' decisions. Although more and more scholars at home and abroad have done various researches on online shopping reviews, few people use Chinese online shopping reviews as the corpus. Therefore, it is meaningful to study online shopping reviews in China from the perspective of evaluation theory. This article selects 900 Chinese online shopping reviews as corpus from Taobao. Quantitative and qualitative research methods were used to analyze. The frequency and distribution of various evaluation resources were calculated by quantitative analysis. The significance of statistical results is analyzed by qualitative method. This paper mainly studies three questions: 1) what are the different forms of implementation of evaluation resources? What is the frequency of different evaluation resources in online shopping reviews in China? (what is the distribution of different evaluation resources in high praise?) how do online shopping reviews in China achieve interpersonal meaning through evaluation resources? Through data analysis, the study found that different evaluation resources are reflected by words such as "like", "worth", "sure enough", "I think", "less", "bit" and so on. Statistics show that there are 5740 evaluation resources in the selected examples. Among them, the most expressed attitude, a total of 3784. The second was graded resources, 1137, accounting for 24% of all evaluation resources, and the least one was intervention resources, 549, accounting for 10% of all evaluation resources. Second, the highest number of evaluation resources were included in the reviews, with a total of 2163. The second is poor evaluation, a total of 1720 evaluation resources. A total of 1 587 evaluation resources were included in the middle evaluation. The three kinds of evaluation contain the most resources of attitude, followed by differential resources, intervention resources are the least. Third, online shopping reviews can achieve interpersonal meaning. Consumers use attitude resources to express their attitudes, thereby persuading potential consumers to buy goods or give up buying ideas. Consumers use intervention resources to take a stand and establish friendly relationships with potential consumers in order to achieve the purpose of persuasion. They also use extreme resources to align with potential consumers, while giving them a clearer understanding of commodity merchants and others. This paper makes up for the deficiency of Chinese consumers' online shopping comment research, and puts forward some suggestions on the research direction of Chinese consumers' online shopping reviews from the perspective of evaluation theory.
【学位授予单位】：东北师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：H136

【参考文献】