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Identifying Linguistically Relevant Communities of Practice on Twitch
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Identifying Linguistically Relevant Communities of Practice on Twitch
This paper argues that, when it comes to modeling language variation and change on the video game streaming platform Twitch, it is necessary to consider "meso-level" communities of practice, i.e. communities of practice that are smaller than the full video game community, yet larger than the usual level of analysis in recent linguistics studies: communities associated with individual Twitch channels. We present a computational method for identifying these linguistically relevant communities of practice and show how this method can be useful for analyzing quantitative patterns of sociolinguistic variation in a corpus composed of the chat transcripts of 15 streamers of the game Elden Ring: Nightreign.
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