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BEASTling: A software tool for linguistic phylogenetics using BEAST 2.

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  • 1School of Psychology, University of Auckland, Auckland, New Zealand.

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|August 11, 2017
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Summary
This summary is machine-generated.

BEASTling is a new open-source software tool that simplifies Bayesian phylogenetic analysis for linguistic data. It makes complex computational models of language evolution more accessible to historical linguists.

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Area of Science:

  • Computational Linguistics
  • Bioinformatics
  • Evolutionary Biology

Background:

  • Bayesian phylogenetic analysis is a powerful tool for understanding language evolution.
  • Preparing linguistic data for such analyses can be complex and time-consuming.
  • There is a need for accessible tools to bridge the gap between computational modelers and linguists.

Purpose of the Study:

  • To introduce BEASTling, an open-source software tool designed to streamline the preparation of Bayesian phylogenetic analyses for linguistic data.
  • To enhance the accessibility of Bayesian phylogenetic methods for historical linguists.
  • To foster collaboration between computational linguists and domain experts.

Main Methods:

  • BEASTling transforms human-readable configuration files into BEAST 2-compatible XML files.
  • It integrates with the Glottolog language catalog for data filtering and monophyly constraints.
  • Supports the Cross-Linguistic Linked Data (CLDF) format for easy data incorporation.

Main Results:

  • BEASTling simplifies dataset preparation for Bayesian phylogenetic analyses of linguistic data.
  • The tool facilitates the use of Glottolog data, including language family filtering and geographic data assignment.
  • It enables backward compatibility with Glottolog classifications through monophyly constraints.

Conclusions:

  • BEASTling lowers the barrier to entry for historical linguists using Bayesian phylogenetic analysis.
  • The software promotes greater accessibility and collaboration in the field of computational models of language evolution.
  • It facilitates the integration of diverse linguistic datasets into phylogenetic analyses.