This study used the Latent Dirichlet Allocation (LDA) topic model to analyze pre-service teachers' views on the nature of science (NOS). This approach can be used to automate the classification of documents, and at the same time, the researcher does not need to deduce with a NOS framework prior to evaluation. Participants were 155 pre-service teachers studying at the Shandong Normal University in China. To gather our data, we used an open questionnaire, namely, the Views of Nature of Science Questionnaire-Form C (VNOS-C). LDA topic modeling was used to classify the document, which was divided into 12 topics. By comparing the LDA topic modeling results with the theoretical framework behind the VNOS-C questionnaire, we categorized these 12 topics into eight descriptive aspects of the NOS: The Empirical Nature of Scientific Knowledge, Observation, Inference, and Theoretical Entities in Science, Scientific Theories and Laws, The Theory-Laden Nature of Scientific Knowledge, The Social and Cultural Embeddedness of Scientific Knowledge, The Myth of The Scientific Method, The Tentative Nature of Scientific Knowledge, and The Nature of Scientific Theory. The results show that pre-service teachers usually hold naive or mixed views of the NOS. In addition, each aspect of NOS is not independent of each other but interrelated and influencing each other. In the future, more consideration can be given to the relationship between each aspect of NOS.