摘要：

Abstract:

【Purpose/significance】In the face of the continuous innovation of technology and the increasing work needs of the masses,

government departments have not shown their due efficiency, and the information coordination status of various departments in prac⁃

tice is not ideal. Therefore, how to effectively evaluate the current situation of information coordination of smart government has be⁃

come a problem worth studying, to identify and measure the synergy degree of smart government information collaborative network

structure is important.【Method/process】This paper proposes a method to identify the synergy degree of smart government information

collaborative network structure based on complex network theory, and takes the entropy of network structure as the measure index of

the synergy degree of information collaborative network structure. The smart government of Shenzhen is taken as a case study to verify

the feasibility and effectiveness of this method.【Result/conclusion】The research shows that the entropy of network structure, as an in⁃

dex to measure the heterogeneity of network structure, has a good explanatory power in the measure of synergy degree of intelligent

government information collaborative network. Smart government information collaborative network intuitively reflects the collabora⁃

tive status among various government departments. Through the identification of key nodes and the measurement of the synergy degree

of network structure, the overall situation of smart government services can be effectively evaluated, thus providing relevant basis for

improving the efficiency of government services and simplifying the processing process.【Innovation/limitation】This paper constructs

the intelligent government information collaborative network of Shenzhen City through the method of complex network, and evaluates

the degree of collaboration of the intelligent government information collaborative network of Shenzhen City with the network structure

entropy, which provides a theoretical basis for the collaborative construction of the intelligent government information. This study also

has limitations. How to make an effective comprehensive evaluation of the information collaborative network structure and how to opti⁃

mize the information collaborative network by using the connection between the core nodes of the information collaborative network

structure is not mentioned in this paper, which also becomes the focus of subsequent studies.