Customer Sentiment in Web-Based Service Interactions: Automated Analyses and New Insights

Galit B. Yom-Tov, Shelly Ashtar, Daniel Altman, Michael Natapov, Neta Barkay, Monika Westphal, Anat Rafaeli

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

We adjust sentiment analysis techniques to automatically detect customer emotion in on-line service interactions of multiple business domains. Then we use the adjusted sentiment analysis tool to report insights about the dynamics of emotion in on-line service chats, using a large data set of Telecommunication customer service interactions. Our analyses show customer emotions starting out negative and evolving into positive as the interaction ends. Also, we identify a close relationship between customer emotion dynamicsduring the service interaction and the concepts of service failure and recovery. This connection manifests in customer service quality evaluationsafter the interaction ends. Our study shows the connection between customer emotion and service quality as service interactions unfold, and suggests the use of sentiment analysis tools for real-time monitoring and control of web-based service quality.

Original languageEnglish
Title of host publicationThe Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018
PublisherAssociation for Computing Machinery, Inc
Pages1689-1697
Number of pages9
ISBN (Electronic)9781450356404
DOIs
StatePublished - 23 Apr 2018
Externally publishedYes
Event27th International World Wide Web, WWW 2018 - Lyon, France
Duration: 23 Apr 201827 Apr 2018

Publication series

NameThe Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018

Conference

Conference27th International World Wide Web, WWW 2018
Country/TerritoryFrance
CityLyon
Period23/04/1827/04/18

Keywords

  • customer satisfaction
  • customer service
  • sentiment analysis

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