Analysis of Application Data Mining to Capture Consumer Review Data on Booking Websites

Abstract

The rapid development of the Internet has led to the prevalence of big data analysis. Data mining is crucial to extracting potentially valuable information from big data and has therefore received considerable attention from researchers. Python is a common programming language used in data mining. Because of its rich database and robust capacity for scientific calculations, Python is considered an irreplaceable tool for data mining. This study adopted Python to perform a data mining analysis on visitor comments on Booking.com. The study was divided into several stages, namely, data source selection, data acquisition, data saving, data preprocessing, indexing of comments on Booking.com through the Python-based Scrapy framework, and user operation simulation through Selenium to analyze the performance of the spider program. Data mining can be used to identify useful information, which can serve as references for consumers to make purchase decisions. Extraction of data from booking sites through spider programs enables site administrators to attract more visitors. Analysis of extracted data also facilitates the elimination of misjudged comments and helps hotels improve their service quality, hardware, and personnel training.