Abstract: Information dimension reveals the fractal characteristics of complex networks from the perspective of information content. The existing information dimension algorithm of weighted network only uses the box size selection rules of the box coverage algorithm of weighted network. This paper further considers the information of edge weight between nodes in the box, and redefines the probability of the box containing information as the ratio of the sum of the strength of all nodes in the box to the sum of the strength of all nodes in the network. A strength information dimension algorithm is proposed to analyze the fractal characteristics of weighted networks. This algorithm is applied to two kinds of constructed weighted networks, Sierpinski and Cantor Dust, and the strength information dimension calculated is very close to the theoretical dimension of the network, and the algorithm is compared with the existing information dimension algorithm and box covering algorithm of weighted network in three real weighted networks. The experimental results show that the three algorithms all measure the fractal characteristics of the weighted network, but the algorithm in this paper is slightly better in terms of fitting effect and fitting error.