Abstract
We examine the effects of heterogeneous social interactions in a numerical model of language change based on the evolutionary utterance based theory developed by Croft. Two or more variants of a linguistic variable compete in the population. Social interactions can be separated into a symmetric weighted network of social contact probabilities, and asymmetric weightings given by speakers to each other’s utterances, that is, social influence. Remarkably, when interactions are symmetric between speakers, the network structure has no effect on the mean time to consensus. On the other hand large disparities in social influence, even in rather homogeneous networks, can dramatically affect mean time to reach consensus (fixation). We explore a range of representative scenarios, to give a general picture of both aspects of social interactions, in the absence of explicit selection for any particular variant.
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Baxter, G.J. (2016). Social Networks and Beyond in Language Change. In: Mehler, A., Lücking, A., Banisch, S., Blanchard, P., Job, B. (eds) Towards a Theoretical Framework for Analyzing Complex Linguistic Networks. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47238-5_12
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DOI: https://doi.org/10.1007/978-3-662-47238-5_12
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