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Model-based sentiment analysis of customer satisfaction for the Jordanian telecommunication companies

机译:基于模型的约旦电信公司客户满意度情绪分析

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Nowadays, social networks are considered to be the most useful data source for analysis trend. The data can be used for different goals, for instance, the commercial companies use the Facebook pages to discover their customer satisfaction of the provided services. This research targets sentiment analysis the customers' posts on the formal Facebook pages of the Jordanian telecommunication companies. The dataset of this paper is collected from three main Jordanian telecommunication companies: Orange, Zain, and Umniah. A supervised based approach including K Nearest Neighbors, Support Vector Machine, Naïve Bayes, and Decision Trees are applied and a comparison between them is provided in term of accuracy metrics. In this study, we introduce a model that is able to make a sentiment analysis of the customer posts on Facebook written in Jordanian dialect.
机译:如今,社交网络被认为是分析趋势最有用的数据源。数据可以用于不同的目标,例如,商业公司使用Facebook页面来发现其客户对所提供服务的满意度。这项研究旨在对约旦电信公司在Facebook正式页面上的客户帖子进行情绪分析。本文的数据集是从约旦的三个主要电信公司收集的:Orange,Zain和Umniah。采用了基于监督的方法,包括K个最近邻,支持向量机,朴素贝叶斯和决策树,并根据准确性指标对它们进行了比较。在这项研究中,我们介绍了一种模型,该模型能够对以约旦方言编写的Facebook上的客户帖子进行情感分析。

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