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

View Sample PDF

Author(s): Zehra Nur Canbolat (Istanbul Medipol University, Turkey)and Fatih Pinarbasi (Istanbul Medipol University, Turkey)
Copyright: 2022
Pages: 24
Source title: Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-6303-1.ch070

Keywords: Data Analysis and Statistics / Data Mining / Engineering Science Reference / Library & Information Science

Purchase

View Using Sentiment Analysis for Evaluating e-WOM: A Data Mining Approach for Marketing Decision Making on the publisher's website for pricing and purchasing information.

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.

The IRMA Community

Research IRM

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

Purchase

Abstract

Related Content

IRMA Sponsors