This paper presents a method for creating lexicons that represent the specific language used in online health communities. Focusing on a breast cancer community, the study generates lexicons for three semantic categories: medications, symptoms and side effects, and emotions. It demonstrates that a data-driven approach can effectively capture the unique language of these communities and improve the coverage of general-purpose terminologies. The paper also provides access to the generated lexicons and code for further research use.