Modeling simulation method of language competition model based on agent social circle network

Abstract

The invention relates to a modeling simulation method of a language competition model based on an agent social circle network, which belongs to the field of computer simulation. The method comprises the following steps of firstly establishing a language communication network based on a social circle theory; setting language types in different population ratios; then establishing a language spreading probability model; adding a birth rate, a death rate and society migration population; finally performing the modeling simulation for the competitive spreading of language by utilizing the established social circle network. According to the method, statistics can be made for multiple real social network characteristics, and the coupling evolution mechanism of a large-scale society network can be flexibly described; the individual network scale is different due to different social radius, the clustering coefficient is high, and the scale is dynamically varied along the time; the strong connection relation inside the circle can be changed by the migration of population, and the weak connection in the circle also can be changed; the complicated association and heterogeneity of a layering structure of the social circle and the social network of people can be expressed.

Description

technical field [0001] The invention relates to a modeling simulation method of a language competition model based on an agent social circle network, and belongs to the field of computer simulation. Background technique [0002] Traditional models of language competition dynamics based on differential equations limit the explanatory value of the models due to their overly ideal assumptions. Existing studies on language communication models based on complex networks mainly focus on the impact of network topology features, such as small-world features, scale-free features, high clustering features, and network modularity, on the spread of language communication. On the one hand, there is a large gap between the constructed language communication network and the actual social network, and it is difficult to explain it with social theory. On the other hand, little attention has been paid to the change of the network structure over time. It is based on a static network. [0003...

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Problems solved by technology

Therefore, the static language network model cannot represent the real social language communication network very well.

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