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The study of language shift, the replacement of one language by another in a community, or subgroup of a speech community, is a prime topic for sociolinguistic analysis: shift is almost always the result of social factors. This paper argues for focusing research on the study of shift in process and, to that end, studying the different kinds of speakers in shifting communities. The prevalent response to massive, global language shift by linguists is language documentation. Although the need for documentation is clear, there have been inadvertent consequences: valorizing last speakers, promoting linguistic purism, and devaluing L2 language learners who, in many communities, represent the future of the language. The urgency of documenting and describing languages with relatively small numbers of elderly speakers has led the linguistic community to focus almost exclusively on such groups and ignore both larger speech communities in earlier stages of shift, and overlook the wide range of speaker types in shift communities. From a social standpoint, the result is that we are often failing to do the language work in precisely those communities where reversing language shift is still relatively easy. From a scientific standpoint, we are missing the opportunity to study language change in process, and missing the chance to study speaker variation in a shift situation. Variation in proficiency and performance across shifting speakers is not random but systematic and correlates with a set of social and cognitive factors.
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Characterizing English Variation across Social Media Communities with BERT
Much previous work characterizing language variation across Internet social groups has focused on the types of words used by these groups. We extend this type of study by employing BERT to characterize variation in the senses of words as well, analyzing two months of English comments in 474 Reddit communities. The specificity of different sense clusters to a community, combined with the specificity of a community’s unique word types, is used to identify cases where a social group’s language deviates from the norm. We validate our metrics using user-created glossaries and draw on sociolinguistic theories to connect language variation with trends in community behavior. We find that communities with highly distinctive language are medium-sized, and their loyal and highly engaged users interact in dense networks.
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- Award ID(s):
- 1813470
- PAR ID:
- 10274010
- Editor(s):
- Daelemans, Walter
- Date Published:
- Journal Name:
- Transactions of the Association for Computational Linguistics
- Volume:
- 9
- ISSN:
- 2307-387X
- Page Range / eLocation ID:
- 538-556
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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