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Using Sentiment Analysis for Evaluating e-WOM: A Data Mining Approach for Marketing Decision Making

Using Sentiment Analysis for Evaluating e-WOM: A Data Mining Approach for Marketing Decision Making
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Author(s): Zehra Nur Canbolat (Istanbul Medipol University, Turkey)and Fatih Pinarbasi (Istanbul Medipol University, Turkey)
Copyright: 2020
Pages: 23
Source title: Exploring the Power of Electronic Word-of-Mouth in the Services Industry
Source Author(s)/Editor(s): Sandra Maria Correia Loureiro (Instituto Universitário de Lisboa, Portugal)and Hans Ruediger Kaufmann (University of Applied Management Studies, Germany)
DOI: 10.4018/978-1-5225-8575-6.ch007

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Abstract

Electronic word of mouth is one of the keys elements for marketing decision making. e-WOM has been focus of marketing research as technology and social media become larger part of consumers' lives. This study set out to examine e-wom concept with sentiment analysis methodology in service industry context. The structure of study is twofold including theoretical backgound of related concepts and application section. Theoretical background section contains electronic word of mouth, new consumer and sentiment analysis concepts, and included selected studies for sentiment analysis. The application section which this study has focus on includes a three-stage plan for sentiment analysis practices. Each stage has three different scenarios. One algorithm and one real-life application for each stage are included. Nine scenarios for different service organizations imply that sentiment analysis supported with other methodologies can contribute to understanding of electronic word of mouth.

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