The dynamic interplay between economic conditions and consumer sentiment has become increasingly crucial in the hospitality industry, where online reviews significantly influence consumer choices. This thesis examines the impact of economic factors, like GDP and CPI, on guest sentiment in Swedish hotel reviews. Using logistic regression models and natural language processing (NLP) techniques, such as AspectBased Sentiment Analysis (ABSA) and LLaMA 3, guest reviews are analyzed to identify key drivers of satisfaction, such as room quality, service, and cleanliness. The results show that these hotel attributes significantly influence positive guest sentiment, while economic factors like rising prices can have a negative effect. Interaction models further highlight how guest sentiment is shaped by the combination of hotel features and economic conditions. These findings offer valuable insights for hotel managers to improve guest satisfaction by focusing on critical service areas and responding to economic changes.