  Due to the rapid development of non-face-to-face services due to the corona
virus, commerce through the Internet, such as sales and reservations, is
increasing very rapidly. Consumers also post reviews, suggestions, or judgments
about goods or services on the website. The review data directly used by
consumers provides positive feedback and nice impact to consumers, such as
creating business value. Therefore, analysing review data is very important
from a marketing point of view. Our research suggests a new way to find factors
for customer satisfaction through review data. We applied a method to find
factors for customer satisfaction by mixing and using the data mining
technique, which is a big data analysis method, and the natural language
processing technique, which is a language processing method, in our research.
Unlike many studies on customer satisfaction that have been conducted in the
past, our research has a novelty of the thesis by using various techniques. And
as a result of the analysis, the results of our experiments were very accurate.
