The source code for our paper "Treat the Word As a Whole or Look Inside? Subword Embeddings Model Language Change and Typology" accepted to the 1st International Workshop on Computational Approaches to Historical Language Change 2019.

We use a variant of word embedding model that incorporates subword information to characterize the degree of compositionality in lexical semantics. Our models reveal some interesting yet contrastive patterns of long-term change in multiple languages: Indo-European languages put more weight on subword units in newer words, while conversely Chinese puts less weights on the subwords, but more weight on the word as a whole. Our method provides novel evidence and methodology that enriches existing theories in evolutionary linguistics. The resulting word vectors also has decent performance in NLP-related tasks.

@inproceedings{xu2019lchange,
  author = {Xu, Yang and Zhang, Jiasheng and Reitter, David},
  title = {Treat the Word As a Whole or Look Inside? Subword Embeddings Model Language Change and Typology},
  booktitle = {Proceedings of the 1st International Workshop on Computational Approaches to Historical Language Change},
  year = 2019, 
  address = {Florence, Italy}
}