Topic modeling was used to identify the most discussed topics in news articles from Reuters. The researchers used a method called Latent Dirichlet Allocation (LDA) to analyze the articles and extract key topics and keywords. By training a generic LDA model on Wikipedia articles, they were able to successfully recommend interesting content to users based on their preferences. This approach helps classify documents, extract dominant topics, and make correlations with user interests.