A Bayesian nonparametric mixture model for studying universal patterns in color naming
作者：
Highlights：
• Universal color naming patterns were uncovered using a Bayesian nonparametric model.
• Members from a language were found in multiple clusters, highlighting diversity.
• Results provide insight into the properties of systems at time of data collection.
• Implementation shows how machine learning can be tailored for the social sciences.
摘要
•Universal color naming patterns were uncovered using a Bayesian nonparametric model.•Members from a language were found in multiple clusters, highlighting diversity.•Results provide insight into the properties of systems at time of data collection.•Implementation shows how machine learning can be tailored for the social sciences.
论文关键词：Bayesian nonparametric models,Machine learning,Color naming,Universality
论文评审过程：Received 12 October 2020, Revised 24 November 2020, Accepted 26 November 2020, Available online 23 December 2020, Version of Record 23 December 2020.
论文官网地址：https://doi.org/10.1016/j.amc.2020.125868
