A related study on deep-learning-based opinion leader identification and influence analysis in social networks

In this paper, we study the problem of key node identification in social networks and further analyse the influence of nodes in Twitter networks. We introduce a variety of node importance evaluation metrics such as centrality metric, PageRank algorithm, including HITS algorithm and SALSA algorithm, and combine a variety of features such as user interaction frequency, posting timeliness and content quality, which are used to improve the prediction ability of the model. By applying graph neural network (GNN) data analysis tools, graph attention network (GAT) and graph convolutional network (GCN), which capture the complex relationships between nodes, the performance of the model and the reliability of the conclusions are enhanced by these armies.