© 2014 IEEE. One of the major benefits of text mining is that it provides individuals with an effective method for analyzing copious amounts of knowledge in the form of texts. Since the olden times, knowledge in medicine was established through recording and analyzing human experiences. This paper presents the first results of the use of text mining techniques to analyze online sources e.g. social networks, blogs, forums, medical literature, medical staff and patients' stories for discovering new knowledge and patterns related to diabetic disease covering diagnosis, diet, medicine, and activities. These finding are being gathered into an online knowledge repository for diabetic patients to access and better manage their diseases. In this research work, we found that the impacts of gaining informative and useful knowledge from a whole other range of data (text sources) besides the ones from medical literatures proved significant in detecting patterns in diabetic diseases that were considered to be insignificant before.