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Improving customer complaint management by automatic email classification using linguistic style features as predictors

机译:通过使用语言样式功能作为预测变量的自动电子邮件分类来改善客户投诉管理

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摘要

Customer complaint management is becoming a critical key success factor in today's business environment. This study introduces a methodology to improve complaint-handling strategies through an automatic email-classification system that distinguishes complaints from non-complaints. As such, complaint handling becomes less time-consuming and more successful. The classification system combines traditional text information with new information about the linguistic style of an email. The empirical results show that adding linguistic style information into a classification model with conventional text-classification variables results in a significant increase in predictive performance. In addition, this study reveals linguistic style differences between complaint emails and others.
机译:客户投诉管理已成为当今商业环境中至关重要的关键成功因素。这项研究介绍了一种通过自动电子邮件分类系统来改进投诉处理策略的方法,该系统将投诉与非投诉区分开来。这样,投诉处理变得更省时,更成功。分类系统将传统文本信息与有关电子邮件语言风格的新信息结合在一起。实验结果表明,将语言样式信息添加到具有常规文本分类变量的分类模型中会大大提高预测性能。此外,这项研究还揭示了投诉电子邮件与其他电子邮件在语言风格上的差异。

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