Construction of the Social Network Information Dissemination Index System Based on CNNs - Han, Weihong; Xiao, Linhe; Wu, Xiaobo; He, Daihai; Wang, Zhen; Li, Shudong (Frontiers in Physics, 2022)
The information dissemination index system is an effective way to measure the dissemination of public opinion events in social networks. Due to the complexity, variability, asymmetry of information, the construction of traditional information dissemination index systems demand excessive reliance on manual intervention, have large deviations, and apply in a limited range. Such shortcomings cannot meet the requirements of constructing an objective, comprehensive, and highly credible index system. Therefore, we propose a method of constructing a multi-level and multi-granular information dissemination index system with complex perspectives. And we use the deep learning method of convolutional neural network to extract the rich convolution features of public opinion events in the information dissemination process. Then we train the weight and form the corresponding of the information dissemination index systems. The experimental results prove that the method we use is superior to other methods and have better performance on the dataset of a specific field.