A new model of Internet addiction tendency based on machine learning

This paper proposes a new model to analysis multi factors that affect internet addiction. Firstly, based on the latest research status and achievements of machine learning, this paper constructs a multi-factor weighted analysis model of Internet addiction tendency. Secondly, in order to analyze the determinants of internet addiction more effectively, this paper designs a deep belief network structure based on the method of machine. Through the training of this network, we can get more accurate weight distribution of various factors in the network structure, so as to extract more effective convolution features of multi-factors. Finally, it gives the compared experimental results which show that this new model can make the internet addiction tendency analysis method be more accurate and effective.