Using Big Data and Text Analytics to Understand How Customer Experiences Posted on Yelp.com Impact the Hospitality Industry

This study combines programming and data mining to analyze consumer reviews extracted from Yelp.com to deconstruct the hotel guest experience and examine its association with satisfaction ratings. The findings show many important factors in customer reviews that carry varying weights and find the me...

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Bibliographic Details
Published inContemporary Management Research Vol. 13; no. 2; pp. 107 - 130
Main Authors Ting, Pei-Ju Lucy, Chen, Szu-Ling, Chen, Hsiang, Fang, Wen-Chang
Format Journal Article
LanguageEnglish
Published 台灣 Academy of Taiwan Information Systems Research 30.06.2017
Subjects
Big Data
Brand loyalty
Customer satisfaction
Data analysis
Data Mining
Electronic commerce
Guest Experience Satisfaction
Hospitality industry
Hotel Management
Hotels & motels
Marketing
Recommender systems
Research methodology
Search engines
Sentiment analysis
Social networks
Social Website
Studies
Text Analytics
User generated content
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Summary:This study combines programming and data mining to analyze consumer reviews extracted from Yelp.com to deconstruct the hotel guest experience and examine its association with satisfaction ratings. The findings show many important factors in customer reviews that carry varying weights and find the meaningful semantic compositions inside the customer reviews. More importantly, our approach makes it possible to use big data analytics to find different perspectives on variables that might not have been studied in the hospitality literature.
ISSN:1813-5498
1813-5498
DOI:10.7903/cmr.17730