Abstract

The importance assessment of dynamic nodes in social networks has been a very challenging problem in the field of social network research. This paper creatively adopts the three-dimensional grey relational degree algorithm, introduces the dimension of time based on the attributes of nodes and nodes, and realizes the screening of important nodes in the dynamic social network. Finally, the algorithm is verified by Facebook data set for three consecutive months, and compared with the result of TOPSIS algorithm, which shows that this algorithm is more practical and accurate.

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