Abstract
With the development of social media, consumers are sharing and spreading information rapidly. Since hotel reviews affect hotel image and reputation, it is important to understand the value of customers in hotel reviews. This is in order to consistently provide hotel quality, maintain brand loyalty and create new customers. Hotel companies need to determine which selection attributes are the most meaningful and relevant in online reviews written by consumers. To accomplish this, hotel reviews were collected using the data analysis tool ‘R’ in the online travel community Trip advisor. The text network was analyzed using UCINET6, Netdraw, and the obtained results were then visualized. The results showed that the frequency and network centrality of the attribute room, cleanliness level, staff ability, kindness level, accessibility, and location were all significantly high factors affecting hotel image and reputation. Furthermore, attributes related to the core product of the hotel are being treated as important evaluation items. Based on these results, theoretical and practical implications for hotel market segmentation and future marketing strategies are suggested.
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