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1.	Noble, Bill, et al. (author) Semantic shift in social networks 2021 In: Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics, August 5 - 6, 2021 Bangkok, Thailand. - Stroudsburg, PA : Association for Computational Linguistics. - 9781954085770 Conference paper (peer-reviewed)abstract Just as the meaning of words is tied to the communities in which they are used, so too is semantic change. But how does lexical semantic change manifest differently across different communities? In this work, we investigate the relationship between community structure and semantic change in 45 communities from the social media website Reddit. We use distributional methods to quantify lexical semantic change and induce a social network on communities, based on interactions between members. We explore the relationship between semantic change and the clustering coefficient of a community’s social network graph, as well as community size and stability. While none of these factors are found to be significant on their own, we report a significant effect of their three-way interaction. We also report on significant word-level effects of frequency and change in frequency, which replicate previous findings.

Noble, Bill, et al. (author)
Semantic shift in social networks
2021
In: Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics, August 5 - 6, 2021 Bangkok, Thailand. - Stroudsburg, PA : Association for Computational Linguistics. - 9781954085770
Conference paper (peer-reviewed)abstract
- Just as the meaning of words is tied to the communities in which they are used, so too is semantic change. But how does lexical semantic change manifest differently across different communities? In this work, we investigate the relationship between community structure and semantic change in 45 communities from the social media website Reddit. We use distributional methods to quantify lexical semantic change and induce a social network on communities, based on interactions between members. We explore the relationship between semantic change and the clustering coefficient of a community’s social network graph, as well as community size and stability. While none of these factors are found to be significant on their own, we report a significant effect of their three-way interaction. We also report on significant word-level effects of frequency and change in frequency, which replicate previous findings.

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