Identification of satisfaction and dissatisfaction factors of hotel customers using natural language processing techniques

This paper proposes a novel approach to identifying the factors that influence satisfaction and dissatisfaction among Algerian hotel customers through the analysis of online customer reviews. Unlike traditional quantitative methods such as questionnaires, this study employs advanced natural language processing techniques to uncover key insights into customer experiences. The study employs natural language processing techniques to extract and analyze data from online customer reviews. This method aims to identify significant concerns and satisfaction factors mentioned by Algerian hotel customers, offering an innovative alternative to conventional survey-based approaches. The analysis revealed that satisfaction factors are specific, tangible aspects of the customer's experience, which can be easily conceptualized. In contrast, dissatisfaction factors are more abstract and challenging to define, which makes them more difficult to comprehend. The paper introduces an innovative approach by leveraging natural language processing to analyze customer reviews, offering a fresh perspective on understanding customer satisfaction and dissatisfaction. This methodology provides valuable insights into customer experiences and highlights the differences in how satisfaction and dissatisfaction are perceived and articulated by customers.