We proposed a method of collecting humorous expressions from an online community-based question-answering (CQA) corpus where some users post a variety of questions and other users post relevant answers. Although the service is created for the purpose of knowledge exchange, there are users who enjoy posting humorous responses. Therefore, the corpus contains many interesting humour communication examples that might be useful in understanding the nature of online communications and variations in humour. Considering the size of 3; 116; 009 topics, it is necessary to introduce automation in the collection process. However, due to the context dependency of humour expressions, it is hard to collect them automatically by using keywords or key phrases. Our method uses natural language processing based on dissimilarity criteria between answer texts. By using this method, we can collect humour expressions more efficiently than by manual exploration: 30 times more examples per hour.