| Summary: | The comments and ratings of the guests on the internet about the hotels they stayed in are
one of the important factors that affect the choice of the guests who are considering staying at the
property. Before booking a hotel, guests can read guest reviews on online travel agencies or travel
platforms and decide accordingly. In this study, the ratings and comments of the guests for the hotels they stayed in were
analyzed by text mining. For this, the comments and scores made in Turkish about the accommodation
facilities in Turkey from an online travel agency were obtained by web mining, and then they were
subjected to text mining. 60252 Turkish guest comments and scores were analyzed in the study.
Accordingly, the average guest rating of accommodation facilities in Turkey is 3.93. Villa type
facilities got the highest score (p=4.22; n=854). The Central Anatolia region (p=4.07; n=5131) got
the highest score as a geographical region, and Nevşehir (p=4.53; n=2320) as a province.
As a result of the text mining applied within the scope of the research, when the most
repeated single words in the hotel comments are grouped according to the scores; It has been found
that the guests do not recommend the facilities they give 1 point, they recommend the facilities they
give 4 and 5 points. It was determined that the guests mostly gave their opinions about the room,
breakfast, water and cleanliness in the facilities they gave low scores. On the other hand, in the
facilities where the guests gave high scores, it was observed that the hotel was clean and the staff
used words expressing that they were interested in the guest.
As a result of the research, the factors that cause dislike and therefore a low score in Turkish
comments on accommodation facilities in Turkey; It has been determined as a result of text mining
that it is related to the problem of room, breakfast, cleaning and hot water. It is seen that the factors
that cause high scores are also related to cleanliness and the interest of the staff. In terms of knowing
the factors related to guest satisfaction, guest complaints and satisfaction; it is thought that it will
contribute to sector managers, entrepreneurs and researchers.
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