BackgroundThe open Suomi24 discussion forum, Finland’s largest topic-centric social media, provides excellent opportunities to study users’ interactions with various contemporary discussion topics. Its easy access and anonymity enable patient and users to seek valuable advices or share their experiences. This paper focuses primarily on cancer health users’ discussion forum and attempts to lie down foundations for content-analysis based approach for identifying psychosocial factors of patient cancer community in Suomi24.MethodThe methodology utilizes to a large extent innovative natural language processing based approach that calls for ontology based construction for identifying the relevant discussion threads in Suomi24 corpus. Next, a co-occurrence analysis with various distance level was employed to quantify the strength of the co-occurring words. Inspired by psychosocial factors analysis in related medical studies, a categorization for psychosocial factors has been put forward and investigated.ResultsThe results overlap to a large extent with some previous findings in clinical studies where the dominance of the social factors is highly reported. An open platform has been put forward to help both researchers and clinicians to study the Suomi24 collected dataset, with the potential correlation analysis with patient records through dedicated electronic medical record databases.ConclusionThis work paves the way for further investigation of medical textual data in order to correlate the finding with patient records as registered in electronic medical records. Besides, the analysis also highlights the challenge of accommodating standard NLP tools to Finnish language where more work is needed in order to match the performance of the available tools in English textual analysis.