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Review-based measurement of customer satisfaction in mobile service: Sentiment analysis and VIKOR approach

机译:基于评论的移动服务客户满意度评估:情感分析和VIKOR方法

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With the rapid growth and dissemination of mobile services, enhancement of customer satisfaction has emerged as a core issue. Customer reviews are recognized as fruitful information sources for monitoring and enhancing customer satisfaction levels, particularly as they convey the real voices of actual customers expressing relatively unambiguous opinions. As a methodological means of customer review analysis, sentiment analysis has come to the fore. Although several sentiment analysis approaches have proposed extraction of the emotional information from customer reviews, however, a lacuna remains as to how to effectively analyze customer reviews for the purpose of monitoring customer satisfaction with mobile services. In response, the present study developed a new framework for measurement of customer satisfaction for mobile services by combining VIKOR (in Serbian: ViseKriterijumsa Optimizacija I Kompromisno Resenje) and sentiment analysis. With VIKOR, which is a compromise ranking method of the multicriteria decision making (MCDM) approach, customer satisfaction for mobile services can be accurately measured by a sentiment-analysis scheme that simultaneously considers maximum group utility and individual regret. The suggested framework consists mainly of two stages: data collection and preprocessing, and measurement of customer satisfaction. In the first, data collection and preprocessing stage, text mining is utilized to compile customer-review-based dictionaries of attributes and sentiment words. Then, using sentiment analysis, sentiment scores for attributes are calculated for each mobile service. In the second stage, levels of customer satisfaction are measured using VIKOR. For the purpose of illustration, an empirical case study was conducted on customer reviews of mobile application services. We believe that the proposed customer-review-based approach not only saves time and effort in measuring customer satisfaction, but also captures the real voices of customers.
机译:随着移动服务的快速增长和传播,提高客户满意度已成为核心问题。客户评论被认为是监测和提高客户满意度的有效信息来源,尤其是当它们传达实际客户的声音时,他们表达了相对明确的意见。作为客户评论分析的一种方法,情感分析已经成为人们关注的焦点。尽管已经提出了几种情感分析方法来从客户评论中提取情感信息,但是,如何有效地分析客户评论以监控移动服务的客户满意度仍然是一个空白。作为回应,本研究通过结合VIKOR(塞尔维亚语:ViseKriterijumsa Optimizacija I Kompromisno Resenje)和情感分析,开发了衡量移动服务客户满意度的新框架。使用VIKOR(这是多准则决策(MCDM)方法的折衷排序方法),可以通过情感分析方案准确衡量移动服务的客户满意度,该方案同时考虑了最大的团体效用和个人遗憾。建议的框架主要包括两个阶段:数据收集和预处理,以及客户满意度的衡量。在第一个数据收集和预处理阶段,利用文本挖掘来编译基于客户评论的属性和情感词字典。然后,使用情感分析,为每个移动服务计算属性的情感分数。在第二阶段,使用VIKOR衡量客户满意度。为了说明的目的,对移动应用程序服务的客户评论进行了经验案例研究。我们相信,所提出的基于客户审查的方法不仅可以节省衡量客户满意度的时间和精力,而且可以捕获客户的真实声音。

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