Enhancing Effectiveness and Efficiency of Customers Reviews Data Collection Through Multithreaded Web Scraping Approach

In recent years, with the spread of the Internet and online applications, various changes have occurred in the tourism business and industries. One of them is the accommodation reservation site. These reservation sites allow users to leave evaluations and reviews of accommodation facilities. Those reviews have a great influence on the preferences of other users and the impact of the reviews become even stronger in the future. This review presents opportunities and challenges for tourism industry and consumer behavior researchers. Reviews provide an opportunity to understand consumer choices, preferences, and behavior. Also, the opportunity to promote products and services based on reviews. Hotels can also use this trend very seriously in their decision making. However, these reviews need to be collected, managed, and analyzed in an effective and efficient manner, and data collection from online platforms is one of the major challenges. We are developing a tool to collect hotels costumers’ reviews called MULARS (Multi-languages Reviews Scrapers) with the aim of efficiently scraping multilingual online reviews. In our previous research, we made it possible to scrape multilingual data [1]. However, faster speed and more effective system of scraping is required for scraping large-scale data. Therefore, we are looking for ways to enhance the performance and effectiveness of the scraping process. In this research, we propose data scraping using multithreading. We implement a multithreaded scraping system and test its performance to demonstrate its improved speed and efficiency. This paper describes the proposed system, and the results of experiment of data collection performances will be presented. Finally, the paper discusses the improvement by adopting the multi-threading, the tool advantages, and future possibilities of the tool applications on the different areas.