Estimating transmission noise on networks from stationary local order
Christopher R. Kitching, Henri Kauhanen, Jordan Abbott, Deepthi Gopal, Ricardo Bermudez-Otero, Tobias Galla
February 2025 

We study networks of nodes characterised by binary traits that change both endogenously and through nearest-neighbour interaction. Our analytical results show that those traits can be ranked according to the noisiness of their transmission using only measures of order in the stationary state. Crucially, this ranking is independent of network topology. As an example, we explain why, in line with a long-standing hypothesis, the relative stability of the structural traits of languages can be estimated from their geospatial distribution. We conjecture that similar inferences may be possible in a more general class of Markovian systems. Consequently, in many empirical domains where longitudinal information is not easily available the propensities of traits to change could be estimated from spatial data alone.

Format:	[ pdf ]
Reference:	lingbuzz/009011 (please use that when you cite this article)
Published in:	Europhysics Letters (EPL) 150(3): 331002
keywords:	linguistic typology, statistical mechanics, complex systems, network science, diachronic stability, geospatial distribution, longitudinal data, spatial data, morphology, syntax, phonology
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