使用大數據與文字探勘分析顧客文字以了解其對飯店產業的影響

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

陳思伶(SZU-LING CHEN)

指導教授 ： 方文昌

國立臺北大學/商學院/企業管理學系/碩士(2016年)

摘要

隨著電子商務的蓬勃發展,旅遊網站與飯店業者也紛紛開始合作推出線上訂房的網站與服務,而這樣的旅遊平台也提供消費者瀏覽與提供回饋意見的地方,隨著時間累積,大量的顧客論也成為重要的研究資料,其代表了線上口碑,且越來越多研究將之利用在大數據的分析,本論文利用文字探勘與計算文字頻率的方式,並進一步加入其他飯店資料等等因素作分析,來探大量線上顧客評論的潛在價值與應用,並期望找出有用的關鍵字來幫助顧客挑選適合的飯店,給予飯店業者營運的參考。

關鍵字

顧客評論 ； 電子商務 ； 數據分析 ； 文字探勘

並列摘要

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.

並列關鍵字

Guest Experience Satisfaction ； Social Website ； Data Mining ； Text Analytics ； Big Data ； Hotel Management

參考文獻

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