Analyzing user reviews in tourism with topic models

User generated content in general and textual reviews in particular constitute a vast source of information for the decision making of tourists and management and are therefore a key component for e-tourism. This paper provides a description of the topic model method with a particular application focus on the tourism domain. It therefore contributes different application scenarios where the topic model method processes textual reviews in order to provide decision support and recommendations to online tourists as well as to build a basis for further analytics. In the latter case the delivery of additional semantics helps digging into the enormous amounts of data that are continuously collected in present time. The contribution therefore consists of new models based on the topic model method and results from experimenting with user generated review data on restaurants and hotels.