Using Natural Language Processing to Evaluate Airbnb Reviews

This project was a case study on natural language processing (NLP), specifically Topic Modeling and Aspect-Based Sentiment Analysis (ABSA). This project was a case study on natural language processing (NLP), specifically Topic Modeling and Aspect-Based Sentiment Analysis (ABSA). The data I used was publicly available from Airbnb reviews for listings in the Denver, Colorado, area. As online purchasing has become second nature for many consumers, many have come to rely on the online reviews left by previous shoppers. But shoppers aren’t the only ones who could benefit from the online feedback. Businesses have a lot to gain by extracting the aspects of the products that their customers feel most assertive about, either good or bad. ABSA uncovered the guest’s most substantial feelings about their stay in this case study. This level of detail can help an Airbnb host market their listing to attract more guests. Knowing what previous guests have enjoyed about their stay, a host can include these aspects in the listing description or other marketing materials. 

On the other hand, if the guest did not like the drippy faucet in the bathroom or the loud neighbor upstairs, the host can address these issues quickly. The key is the host needs to know this information promptly. NLP can provide a competitive business advantage because problems can be addressed quicker, and the hosts can share compliments with others sooner.