A MODEL TO DETECT SOCIAL NETWORK MENTAL DISORDERSUSING AI TECHNIQUES.
Dr.Tummapudi.Subha Mastan Rao, Dr.Vijaya sri kompalli, UdayaSri Kompalli · Journal of Critical Reviews · 2020
Nowadays the users of social network are increasing drastically worldwide. This platform become very useful for sharing information, discussing on various issues, Even majority of their active time they are spending on social medias like tweeter, face Book etc. Due to this physical human relations are damaging, and users are addicted to internet and frequent checking of tweeter, Facebook etc, Net compulsion. Recent surveys telling that there is a relation between mental health and social network behaviour. Still it is unclear how this mental illness and social networks are related. In this paper we are going propose a model to to find out mental disorders using social network data analysis, in this work we have collected the data from twitter and manually labelled that data into two classes one is depressive and other is normal then then data pre-processing was performed then it is divided into training and testing sets, training data is used to build the model by making navie bayes classifier to learn from the data. Once model is build it was tested with the testing set and obtained results with high Accuracy around 92.3. So usually doctor need to find metal disorders they will fire some questions to the patient based on that doctor detects mental illness but in this model we can able to detect mental disorders without consulting patient based on their social network behaviour analysis.