近年來，旅遊市場持續蓬勃發展，帶來無數商機。而台灣在2017年，更被世界經濟論壇（World Economic Forum, WEF）評比為全球觀光競爭力第30名、亞洲第7名，可見台灣觀光產業的實力與競爭優勢。故本研究挑選台灣觀光產業中，發展甚早且十分具有代表性的休閒農業作為研究背景。而本研究與過去線上評論研究最大的不同在於研究方法的使用，本研究以大數據工具爬取獲得「休閒農場服務認證」之37家優良休閒農場在Google Map總計共12,754則線上評論，透過更完整的大量樣本資料，進而萃取出隱藏在線上評論之中的有用資訊，以提出更精準的分析。
透過本研究，將37家優良農場的141個關鍵屬性分成15類，並與專家制定的「休閒農場服務認證」指標進行比較，探討兩者之間的異同。此外，本研究更將關鍵屬性進行兩種視覺化處理─市場定位圖與文字雲。藉由視覺化，發掘更多實務方面的意涵。而本研究也展現了在大數據時代下，不同的線上評論研究方法，並以遊客的角度另行檢視「休閒農場服務認證」，提供農場主思考及制定為迎合遊客的經營指標策略，以及作為官學界日後修改農場指標時的參考建議。

Recently, the tourism market keeps growing, which brings amounts of business opportunities. In 2017, Taiwan ranks 30th in global travel and tourism competitiveness, 7th in Asia. This report result shows that Taiwan has highly competitiveness in global tourism market. Because of this reason, we choose leisure industry as study background, which has developed for many years and can represent Taiwan’s tourism industry. Different from other study, we use a new methodology (text mining) to analyze online reviews. By big data tools, we parse 12,754 travelers’ reviews from Google Maps. In this article, we use the big open data as our sample in order to dig more meaningful information.
In this article, we put 37 outstanding leisure farms’ 141 key attributes into 15 categories, and compare the cluster result with Taiwan Leisure Farm Certification. Moreover, we also transform the key attributes into 2 types of visualization charts (marketing positioning map and wordcloud), which have wider implication. In this article, we contribute not only the different methodology for online reviews in Era of Big Data, but also the management suggestions from travelers’ points for the owners of leisure farms and the authority.

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