This study employs big data analytics to examine customers’ waiting experiences in restaurants, a critical component of the broader hospitality and tourism industry. Drawing upon a large corpus of online reviews, the analysis uses topic modeling to identify four salient themes that emerge?waiting, food, servicescape, and service quality?informing the way in which customers perceive and evaluate dining experiences. Two subsequent regression analyses reveal a significant negative relationship between waiting-related comments and overall review ratings, underscoring the disproportionate influence of waiting experiences in shaping customer satisfaction. These findings offer valuable insights for hospitality and tourism practitioners and researchers aiming to deepen their understanding of how waiting times and experiences can impact service perceptions and overall consumer evaluations in restaurant contexts.