A Study on Maximising the Influence of Social Network Nodes Based on a Comprehensive Influence Hierarchy Model: Structural Analysis and Optimisation of Information Dissemination

The work of network power is related to the construction of public opinion and the management of information dissemination, which is crucial to the development of industry and information technology. It has been a key issue to study how to maximise positive information influence in social network information dissemination. This study focuses on network structure and node influence distribution, and proposes a comprehensive influence level model (CILM) and an innovative node influence factor. The factor integrates the influence level and node degree attributes to provide a basis for node influence assessment. Further, the Neighbour Influence Traversal Algorithm (NITA) and Influence Cascade Transfer Algorithm (ICTA) are designed to optimize the node influence calculation through the network structure and information dissemination characteristics. Experimentally, it is proved that CILM and related algorithms are significantly better than other methods in terms of accuracy and running time, and provide an effective tool for the optimisation of information dissemination in social networks.