A decentralized route to the origins of scaling in human language
This addresses the origins of linguistic scaling patterns for researchers in computational linguistics and complex systems, but it is incremental as it builds on prior work on conflicts of interest in communication.
The study tackled the problem of explaining the emergence of Zipf's law in human language by developing a computational multi-agent language game based on a parameter measuring participants' interests, finding that at critical parameter values, a human-like vocabulary with scaling properties appears, suggesting self-organization from local interactions.
The Zipf's law establishes that if the words of a (large) text are ordered by decreasing frequency, the frequency versus the rank decreases as a power law with exponent close to $-1$. Previous work has stressed that this pattern arises from a conflict of interests of the participants of communication. The challenge here is to define a computational multi-agent language game, mainly based on a parameter that measures the relative participant's interests. Numerical simulations suggest that at critical values of the parameter a human-like vocabulary, exhibiting scaling properties, seems to appear. The appearance of an intermediate distribution of frequencies at some critical values of the parameter suggests that on a population of artificial agents the emergence of scaling partly arises as a self-organized process only from local interactions between agents.