  Various efforts in the Natural Language Processing (NLP) community have been
made to accommodate linguistic diversity and serve speakers of many different
languages. However, it is important to acknowledge that speakers and the
content they produce and require, vary not just by language, but also by
culture. Although language and culture are tightly linked, there are important
differences. Analogous to cross-lingual and multilingual NLP, cross-cultural
and multicultural NLP considers these differences in order to better serve
users of NLP systems. We propose a principled framework to frame these efforts,
and survey existing and potential strategies.
