A Novel Hybrid Model for Stress Detection with Convolutional Neural Networks
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Abstract
Psychological wellness conditions influence a noteworthy level of the world’s
population every year. The stress investigation of emotional wellness phenomena in
openly accessible social networking sites like Twitter,Sina Weibo and Facebook. A set of
stress-related textual, visual, and social attributes from various aspects are first defined
and then propose a novel hybrid model. The work has demonstrated the utility of online
social information for contemplating despondency, be that as it may, there have been
limited assessments of other mental wellbeing conditions. It is not easy to access the user
posts on their Facebook page. In order to obtain the user data from Facebook, system
have to get the access token from Facebook developer page. The API act as an
intermediate system that will help the system to analysis the user information from the
Facebook page. The system will also help to Recommending users with different links for
psychological counselling centers, soft music or articles to help release their stress
according to users’ stress level
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