Towards personalized health profiling in social network

E-Health industry is expanding considerably due to its effectiveness and efficiency in providing better healthcare services. The concern to get personalized information at one's doorstep is on the rise and social media is filling the gap by connecting users and sharing information. Personalized healthcare information in social media has become the cornerstone, allowing us to investigate innovative ways to effectively utilize its needs. The proposed approach discovers and uses personalized healthcare concepts by analyzing user posts on social networks. The analysis highlights the discrepancies in managing ones health and provides guidelines to overcome them. Methodology includes building user profile by identifying user related topics, emotions and health conditions. We investigated 6000 tweets for diabetic information however, our experimental data-set includes about 4000 tweets as we filtered out unwanted tweets. Smart Clinical Decision Support System (smart CDSS) service utilizes the results generated by our experiment.