DECODING OF PRESSURE OVER NETWORKING SITES
Keywords:
Social interaction, mentally tortured, convolutional neural network, tracking, sentimentAbstract
Stress is one of the major thing what people are suffering from today. Everywhere in office or home people are undergoing stress. It may lead to death or some other deadly diseases like heart attack or depression. The stress of the person can be know through his or her behavior. In today’s era we have a social networking platform where a person shares his thoughts it might be wats app, Facebook or twitter. The kind of details the user is being uploading is taken into the context and the stress level of that person is
detected. In this current study, we discover person’s stress level is very closely connected to that of his/her networks of social-media, and we are using a bulky-scale dataset which is collected from the real-world social platforms like Facebook or twitter to steadily see the correlation of users’ stress states and social interactions. We are proposing a new hybrid model which ensures a factor graph model pooled with Convolutional Neural Network (CNN) to force tweet gratified & social collaboration evidence for detecting stress level
