  The surge of interest in culturally aware and adapted Natural Language
Processing (NLP) has inspired much recent research. However, the lack of common
understanding of the concept of "culture" has made it difficult to evaluate
progress in this emerging area. Drawing on prior research in NLP and related
fields, we propose an extensive taxonomy of elements of culture that can
provide a systematic framework for analyzing and understanding research
progress. Using the taxonomy, we survey existing resources and models for
culturally aware and adapted NLP, providing an overview of the state of the art
and the research gaps that still need to be filled.
