Social Data Analytics by Visualized Clustering Approach for Health Care

Social networks play a vital role in public healthcare systems. Twitter, Facebook, and blogs have millions of health-related content and it is required to filter the data for the reduction of processing cost. A semi-supervised health classifier model is proposed for health care which analyzes the patient condition by symptoms and recommends either suggestions or treatments for the relevant diseases such as influenza, flu, etc. In a proposed system, ailments clusters are defined based on the features of diseases using Visualized Clustering Approach (VCA). The proposed Twitter classifier model effectively works for high-rated risk diseases when compared to the traditional healthcare model. Results are discussed in the experimental study.