EMOTION DETECTION IN EMAIL CUSTOMER CARE. (4th September 2012)

• Record Type: Journal Article
• Authors: Gupta, Narendra; Gilbert, Mazin; Fabbrizio, Giuseppe Di
• Is Part Of: Computational intelligence. Volume 29:Number 3(2013:Aug.)
• Page Start: 489
• Page End: 505
• Publication Date: 2012-09-04
• Subjects: boosting -- customer service -- emotional email -- salient features -- support vector machines -- text classification; Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/j.1467-8640.2012.00454.x
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract : Prompt and knowledgeable responses to customers' email are critical in maximizing customer satisfaction. Such messages often contain complaints about unfair treatment due to negligence, incompetence, rigid protocols, unfriendly systems, and unresponsive personnel. In this paper, we refer to these email messages as emotional email . They provide valuable feedback to improve contact center efficiency and the quality of the overall customer care experience, which in turn results in increased customer retention. We describe a method that uses salient features to identify emotional email in the customer care domain. Salient features in customer care related email are expressions of customer frustration, dissatisfaction with the business, and threats to either leave, take legal action, and/or report to authorities. Compared to a baseline system using word unigram features, our proposed approach significantly improves emotional email detection performance.