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Agent-based Modeling of Language Change in a Small-world Network

Language change has been the subject of numerous studies in linguistics. However, due to the dynamic and complex nature of this phenomenon, and to the difficulty of obtaining extensive real data of language in use, some of its aspects remain obscure. In recent years, nonetheless, research has used computational modeling to simulate features related to variation, change, propagation, and evolution of languages in speech communities, finding compelling results. In this article, agent-based modeling and simulation is used to study language change. Drawing on previous studies, a speech community was modeled using Zachary’s karate club network, a well-established small-world network model in the field of complex systems. Idiolects were assigned through numerical values for each agent. The results demonstrate that the centrality of each agent in the network, interpreted as social prestige, appears to be a factor influencing change. Additionally, the nature of idiolects also seems to impact the spread of linguistic variants in the language change process. These findings complement the theoretical understanding of the language change phenomenon with new simulation data and provide new avenues for research.