In some examples, a system for generating a topic model includes a processor that can process a set of documents to generate training data, wherein each document in the set of documents is associated with one or more users. The processor can also generate a plurality of topic models using the training data, such that each topic model includes a different number of topics. The processor can also generate an evaluation score for each of the topic models based on information about the users associated with the documents included in the training data. The evaluation score describes a percentage of topics that exhibit a specified level of interest from a specified number of users. The processor can also identify a final topic model based on the evaluation scores and store the final topic model to be used in natural language processing.