Modeling and simulation method for language competition model of complex agent network with lexical structure

Abstract

The invention relates to a modeling and simulation method for language competition model of complex agent network with lexical structure and belongs to the field of computer simulation, wherein the method of the invention comprises the steps as follows: firstly establishing a dynamic language communication network according to social network theory; imbedding two monolingual populations on this basis and setting language status for two languages; setting an individual integer string and an internal lexical structure thereof and distributing proportion for floating population; setting birth proportion, death proportion and language genetic proportion for individual; simulating the lexical study and the lexical forgetting among individuals according to a language communication model; finally adjusting social linguistic status, social radius, bilingual genetic probability and language learning rate parameter in the model to observe language grasping condition of the individual. The method of the invention can be used for flexibly describing the mechanism of large-scale social network coupling evolution; and reflecting a macroscopic competitive situation among different linguistic types, which are expressed by language interior micro-structure evolution of different speakers via communication and competition.

Description

technical field [0001] The invention relates to a modeling and simulation method of a language competition model of a complex agent network with a lexical structure, and belongs to the field of computer simulation. Background technique [0002] The traditional language competition dynamics model based on differential equations limits the explanatory value of the model due to its too ideal assumptions. At present, the complex agent network model comprehensively considers the social structure of language, population density, language status and the influence of bilingual factors on language coexistence, and has made important progress in the study of language competition dynamics. However, there are still the following problems: (1) Network The static network is mainly used, and the dynamic characteristics of the social network are not considered. However, in the real social contact network, the network topology changes due to the flow of people within or between regions, whi...

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Problems solved by technology

[0002] Traditional differential equation-based models of linguistic competition dynamics limit the explanatory value of models due to overly ideal assumptions

At present, the complex agent network model comprehensively considers the social structure of language, population density, language status and the influence of bilingual factors on language coexistence, and has made important progress in the study of language competition dynamics, but there are still the following problems: (1) network Focusing on static networks, without considering the dynamic characteristics of social networks

(2) The migration probability of a node's language use type in the language exchange competition network is determined by the proportion of the number of people in a certain language in the neighborhood of the node, the status of the language, etc. The language has no internal structure (such as vocabulary), and the language cannot be considered. The dynamic process of learning and mastery does not reflect the impact of language use opportunities and frequency on the type of language use and its ability to change in the system

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