This tutorial covers topic modelling in R using Latent Dirichlet Allocation (LDA), including the preparation of text data, the fitting and tuning of topic models, the interpretation and labelling of topics, and the visualisation of topic-document distributions. It is aimed at researchers in digital humanities, corpus linguistics, and the social sciences who want to explore thematic structure in large text collections. This tutorial is part of the Language Technology and Data Analysis Laboratory (LADAL), a free, open-access research infrastructure at the University of Queensland. LADAL provides tutorials, tools, and courses for researchers working with language data. All materials are freely available at https://ladal.edu.au and are part of the Language Data Commons of Australia (LDaCA), funded by ARDC and NCRIS.