Semantic Variation in Online Communities of Practice

By Marco Del Tredici, R. Fern'andez. 2018

43 citations recorded by the source corpus.

We introduce a framework for quantifying semantic variation of common words in Communities of Practice and in sets of topic-related communities. We show that while some meaning shifts are shared across related communities, others are community-specific, and therefore independent from the discussed topic. We propose such findings as evidence in favour of sociolinguistic theories of socially-driven semantic variation. Results are evaluated using an independent language modelling task. Furthermore, we investigate extralinguistic features and show that factors such as prominence and dissemination of words are related to semantic variation.

Subfields: Artificial Intelligence, Cultural Studies, Language and Linguistics, Computational Linguistics & Semantics, Social Sciences & Humanities

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In Artificial Intelligence

In Cultural Studies

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Dong Nguyen

Citations in the corpus

Temporal Adaptation of BERT and Performance on Downstream Document Classification: Insights from Social Media (2021, background): “We thus expect distinctions between subreddits in PSP to be at least partially predictable based on comment text for two reasons: First, because language use differs between subreddits (Del Tredici and Fernández, 2017).”
On learning and representing social meaning in NLP: a sociolinguistic perspective (2021, background): “Furthermore, variation can also occur at the semantic level (Bamman et al., 2014a; Del Tredici and Fernández, 2017; Lucy and Bam-man, 2021).”