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Detecting contact in language trees: a Bayesian phylogenetic model with horizontal transfer

Neureiter, Nico; Ranacher, Peter; Efrat-Kowalsky, Nour; Kaiping, Gereon A; Weibel, Robert; Widmer, Paul; Bouckaert, Remco R (2022). Detecting contact in language trees: a Bayesian phylogenetic model with horizontal transfer. Humanities & Social Sciences Communications, 9(1):205.

Abstract

Phylogenetic trees are a central tool for studying language evolution and have wide implications for understanding cultural evolution as a whole. For example, they have been the basis of studies on the evolution of musical instruments, religious beliefs and political complexity. Bayesian phylogenetic methods are transparent regarding the data and assumptions underlying the inference. One of these assumptions—that languages change independently—is incompatible with the reality of language evolution, particularly with language contact. When speakers interact, languages frequently borrow linguistic traits from each other. Phylogenetic methods ignore this issue, which can lead to errors in the reconstruction. More importantly, they neglect the rich history of language contact. A principled way of integrating language contact in phylogenetic methods is sorely missing. We present , a Bayesian phylogenetic model with horizontal transfer for language evolution. The model efficiently infers the phylogenetic tree of a language family and contact events between its clades. The implementation is available as a package for the phylogenetics software BEAST 2. We apply in a simulation study and a case study on a subset of well-documented Indo-European languages. The simulation study demonstrates that correctly reconstructs the history of a simulated language family, including simulated contact events. Moreover, it shows that ignoring contact can lead to systematic errors in the estimated tree height, rate of change and tree topology, which can be avoided with . The case study confirms that reconstructs known contact events in the history of Indo-European and finds known loanwords, demonstrating its practical potential. The model has a higher statistical fit to the data than a conventional phylogenetic reconstruction, and the reconstructed tree height is significantly closer to well-attested estimates. Our method closes a long-standing gap between the theoretical and empirical models of cultural evolution. The implications are especially relevant for less documented language families, where our knowledge of past contacts and linguistic borrowings is limited. Since linguistic phylogenies have become the backbone of many studies of cultural evolution, the addition of this integral piece of the puzzle is crucial in the endeavour to understand the history of human culture.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Department of Comparative Language Science
07 Faculty of Science > Institute of Geography
06 Faculty of Arts > Zurich Center for Linguistics
08 Research Priority Programs > Language and Space
Dewey Decimal Classification:400 Language
490 Other languages
890 Other literatures
410 Linguistics
910 Geography & travel
Uncontrolled Keywords:General Economics, Econometrics and Finance, General Psychology, General Social Sciences, General Arts and Humanities, General Business, Management and Accounting
Language:English
Date:1 December 2022
Deposited On:22 Jun 2022 09:40
Last Modified:28 Aug 2024 01:35
Publisher:SpringerOpen
ISSN:2662-9992
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1057/s41599-022-01211-7
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  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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