{"title":"Using Big Data and Text Analytics to Understand How Customer Experiences Posted on Yelp.com Impact the Hospitality Industry","authors":"P. Ting, Szu-Ling Chen, Hsiang Chen, W. Fang","doi":"10.7903/CMR.17730","DOIUrl":null,"url":null,"abstract":"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. \n \nKeywords: Big Data, Text Analytics, Data Mining, Social Website, Guest Experience Satisfaction, Hotel Management \n \nTo cite this document: Pei-Ju Lucy Ting, Szu-Ling Chen, Hsiang Chen, and Wen-Chang Fang, \"Using Big Data and Text Analytics to Understand How Customer Experiences Posted on Yelp.com Impact the Hospitality Industry\", Contemporary Management Research, Vol.13, No.2, pp. 107-130, 2017. \n \nPermanent link to this document: \nhttp://dx.doi.org/10.7903/cmr.17730","PeriodicalId":36973,"journal":{"name":"Contemporary Management Research","volume":"13 1","pages":"107"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Contemporary Management Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7903/CMR.17730","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
引用次数: 17
Abstract
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.
Keywords: Big Data, Text Analytics, Data Mining, Social Website, Guest Experience Satisfaction, Hotel Management
To cite this document: Pei-Ju Lucy Ting, Szu-Ling Chen, Hsiang Chen, and Wen-Chang Fang, "Using Big Data and Text Analytics to Understand How Customer Experiences Posted on Yelp.com Impact the Hospitality Industry", Contemporary Management Research, Vol.13, No.2, pp. 107-130, 2017.
Permanent link to this document:
http://dx.doi.org/10.7903/cmr.17730
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