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We review the task of aligning simple models for language dynamics with relevant empirical data, motivated by the fact that this is rarely attempted in practice despite an abundance of abstract models. We propose that one way to meet this challenge is through the careful construction of null models. We argue in particular that rejection of a null model must have important consequences for theories about language dynamics if modelling is truly to be worthwhile. Our main claim is that the stochastic process of neutral evolution (also known as genetic drift or random copying) is a viable null model for language dynamics. We survey empirical evidence in favour and against neutral evolution as a mechanism behind historical language changes, highlighting the theoretical implications in each case.
Societies change through time, entailing changes in behaviors and institutions. We ask how social change occurs when behaviors and institutions are interdependent. We model a group-structured society in which the transmission of individual behavior o
The voter model has been studied extensively as a paradigmatic opinion dynamics model. However, its ability for modeling real opinion dynamics has not been addressed. We introduce a noisy voter model (accounting for social influence) with agents recu
Here we developed a new conceptual, stochastic Heterogeneous Opinion-Status model (HOpS model), which is adaptive network model. The HOpS model admits to identify the main attributes of dynamics on networks and to study analytically the relation betw
Within the context of agent-based Monte-Carlo simulations, we study the well-known majority-vote model (MVM) with noise applied to tax evasion on Stauffer-Hohnisch-Pittnauer (SHP) networks. To control the fluctuations for tax evasion in the economics
In recent times, the research field of language dynamics has focused on the investigation of language evolution, dividing the work in three evolutive steps, according to the level of complexity: lexicon, categories and grammar. The Naming Game is a s