mlsanityData to 7 Oct 2026

Characterizing English Variation across Social Media Communities with BERT

arXiv 2102.06820 ↗First posted 12 Feb 2021cs.CL cs.SIcited by 20

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Abstract (arXiv)

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.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 23 of its 85 references that are in the map. First posted on arXiv 12 Feb 2021.

Builds on

23 of 85 references.

References · 23

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Don't Stop Pretraining: Adapt Language Models to Domains and Taskscited by 1,548
  3. 2020The Pushshift Reddit Datasetcited by 289
  4. 2019Visualizing and Measuring the Geometry of BERTcited by 215
  5. 2020Analysing Lexical Semantic Change with Contextualised Word Representationscited by 92
  6. 2019Does BERT Make Any Sense? Interpretable Word Sense Disambiguation with Contextualized Embeddingscited by 55
  7. 2015Computational Sociolinguistics: A Surveycited by 35
  8. 2015Overcoming Language Variation in Sentiment Analysis with Social Attentioncited by 23
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11 more
  1. 2015Characterizing the Google Books corpus: Strong limits to inferences of socio-cultural and linguistic evolutioncited by 15
  2. 2018Making "fetch" happen: The influence of social and linguistic context on nonstandard word growth and declinecited by 15
  3. 2016Divergent discourse between protests and counter-protests: #BlackLivesMatter and #AllLivesMattercited by 13
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  6. 2018Semantic Variation in Online Communities of Practicecited by 8
  7. 2018AutoSense Model for Word Sense Inductioncited by 7
  8. 2016Sense Embedding Learning for Word Sense Inductioncited by 4
  9. 2017#anorexia, #anarexia, #anarexyia: Characterizing Online Community Practices with Orthographic Variationcited by 3
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 7; 2023: 5; 2024: 3; 2025: 2; 2026: 2.

20 papers.

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  1. 2022Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Modelscited by 187
  2. 2021DEMix Layers: Disentangling Domains for Modular Language Modelingcited by 130
  3. 2023Scaling Expert Language Models with Unsupervised Domain Discoverycited by 59
  4. 2022Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selectioncited by 52
  5. 2025Culture is Not Trivia: Sociocultural Theory for Cultural NLPcited by 40
  6. 2022Words as Gatekeepers: Measuring Discipline-specific Terms and Meanings in Scholarly Publicationscited by 14
  7. 2023DisCGen: A Framework for Discourse-Informed Counterspeech Generationcited by 14
  8. 2022Discovering Differences in the Representation of People using Contextualized Semantic Axescited by 12
  9. 2024ValueScope: Unveiling Implicit Norms and Values via Return Potential Model of Social Interactionscited by 12
  10. 2022What company do words keep? Revisiting the distributional semantics of J.R. Firth & Zellig Harriscited by 8
  11. 2024Toward Informal Language Processing: Knowledge of Slang in Large Language Modelscited by 6
  12. 2022Stability of Syntactic Dialect Classification Over Space and Timecited by 5
8 more
  1. 2023Social Meme-ing: Measuring Linguistic Variation in Memescited by 5
  2. 2022Tracing Semantic Variation in Slangcited by 3
  3. 2024Inducing lexicons of in-group language with socio-temporal contextcited by 2
  4. 2023Syntactic Variation Across the Grammar: Modelling a Complex Adaptive Systemcited by 1
  5. 2025Affect, Body, Cognition, Demographics, and Emotion: The ABCDE of Text Features for Computational Affective Sciencecited by 1
  6. 2023Sentiment Analysis in Digital Spaces: An Overview of Reviewscited by 0
  7. 2026Finding Common Ground: Graded Communal Knowledge in Bluesky Starter Packscited by 0
  8. 2026From Utterances to Networks: Modelling Slang Adoption and Diffusion Across Subredditscited by 0