earticle

영어

As a result of mental health is gradually being valued when psychological illness such as depression gradually enter the public's field of vision, there is an increasing demand for high-quality and influential popular science articles on depression. However, the fact of uneven quality of online popular science articles on depression increase difficulty for the public to distinguish good one. The quality evaluation of popular science article can be regard as influence prediction. We construct a heterogeneous information network to integrate data from social platform and medical platform. And a heterogeneous graph neural network model based on the heterogeneous information network is proposed to predict the influence of popular science articles on depression. This research can help people select high-quality psychology popular science articles easily. It contributes to extend the influence scope of popular science articles and improve the mental health literacy of the whole people.