Abstract: The hierarchy of node influence in complex networks is crucial for the research on network structure and controllability. As for the problem about the hierarchy of node influence in directed and weighted networks, a directed and weighted collective attention flow network is constructed based on massive data of online user behavior. By defining the Hierarchical Position Time(HPT) and position constraint of nodes, an algorithm for measuring and ranking the node influence in directed weighted networks is proposed. The algorithm also considers the topological positions and time series of nodes. Experimental results show that this algorithm can distinguish the hierarchical structure of network, identifying the most influential nodes accurately. It displays certain reference significance and reference value in evaluating the influence of nodes and the controllability of complex networks.
attention flow network,