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

• Main Authors: CHEN,SZU-LING, 陳思伶
• Other Authors: FANG,WEN-CHANG
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/67055472370562629103

碩士 === 國立臺北大學 === 企業管理學系 === 104 === Nowadays, E-commerce systems used by the major Internet organizations, such as Google, Amazon, expedia.com, include highly scalable E-commerce platforms and social media platforms. These companies try to make use of web data that is less structured but composed of rich customer views and behavioral information. However, studies using these unstructured data to generate business value are still under- researched. This paper focuses on exploring the value of customer reviews post on the social media platforms in the hospitality industry by using big data analytic techniques. We aim to find the keywords that can help customer to find a suitable hotel. To be more specific, this study combines programming skills and applies data mining approaches to analyze lots of consumer reviews extracted from Yelp.com to deconstruct hotel guest experience and digging the possible texture that can be applied when searching or booking hotels. More importantly, the new approach we use in this study would make it possible to utilize big data analytics to find different perspectives that might not have been studied in existing hospitality literature. Moreover, it serves as a basis for further research related to unstructured data used in the E-commerce and hospitality industries.