A text analytics approach for mining public discussions in online cancer forum: Analysis of multi-intent lung cancer treatment dataset.

Background: Online cancer forums (OCF) are increasingly popular platforms for patients and caregivers to discuss, seek information on, and share opinions about diseases and treatments. This interaction generates a substantial amount of unstructured text data, necessitating deeper exploration. Using time series data, our study exploits topic modeling in the novel domain of online cancer forums (OCFs) to identify meaningful topics and changing dynamics of online discussion across different lung cancer treatment intent groups.