This repository archives a spatial-temporal dataset characterizing how the word "tea" (茶) spread over the land and sea.
To load the data, use the following command in R:
df = read.csv("tea-sea-cha-land.csv")The R code for tidying the data is in data-generator.R.
We thank @Lchiffon for contributing an interactive map visualization with computed possible tea trade paths for the dataset using his package REmap. The R code for creating the visualization is in plot-remap.R.
World Atlas of Language Structures (WALS) database. Feature 138A: Tea.
Tea if by sea, cha if by land: Why the world only has two words for tea, by Nikhil Sonnad. January 11, 2018.
Tea if by Sea, by Dan Jurafsky. August 3, 2014.