Balanced Health Monitoring System using Stop Words for Social Big Data Applications Sangam M V1, Rath Ramakrushna2, Raju G Appala2, Dinakar R Bala3, Rao G Venkata4 1Associate Professor, Department of CSE, Godavari Institute of Engineering & Technology, Rajahmundry, A.P, India 2Assistant Professor, Department of CSE, Godavari Institute of Engineering & Technology, Rajahmundry, A.P, India 3Associate Professor, Department of MCA, Godavari Institute of Engineering & Technology, Rajahmundry, A.P, India 4Department of CSE, Godavari Institute of Engineering & Technology, Rajahmundry, A.P, India Online published on 2 February, 2019. Abstract As per health care perception depression is a wellbeing concern at global range. Today social media allows the people those who affected can share their experiences through posts. Such experiences are stored in database and can be extracted, analyzing to assist the precautions for drugs from side effects, and other service improvements in their particular disease treatment. In those aspects, social websites related to depression are helpful to extract knowledge or monitoring various types of drugs and its side effects and also for sharing their experiences on depression. We have taken a weighted edge network model for representing social networks activities. The proposed work undergoes with the three steps. The frst step is user activity monitoring, followed by network clustering and module analysis. Whoever the person like a specifc posts belongs to a group and those who are not are belong to other group. We implemented the stop word technique here which is helpful in avoiding the misleading communication on the posts and effcient interaction of user. The statistical analysis of such user interactions are benefcial for health networks to acquire more knowledge on particular disease. This approach enables us all the gatherings took a part and for healthcare improvements in future to the patients of that disease. Top Keywords Data mining, online fora, depression, stop-words technique. Top |