User Recommendation for Detecting Stress with Factor Graph Model
Manepalli Deepika · International Journal for Research in Applied Science and Engineering Technology · 2018
In today's world generally humans feel stress for very small issue that might be for face to face interviews and some other issues, psychological stress is becoming a threat to people's health nowadays. According to worldwide recent survey over half an population feel stress during last two years.With the development of social media more people share their daily activities and they try to interact with their friends through their posts.In this paper, we find that users stress state is closely related to that of his/her friends in social media .First we maintain a set of text related words that is positive, negative, stressed words in the database.The user will identify the stress in the post which was posted by his/her friend and suggest for his/her problem through.Re tweeting can be classified through Factor Graph Model.If a stress word which is not maintained in the database then it fails to identify stress word which was written in the comment.For that the user will recommend a new stress word to the admin.If admin is not maintained in the database what the user will recommended , then admin will include that filter into the database else if admin is already maintaining that word it shows a message that word already exists.