# Semantic Variation in Online Communities of Practice

arXiv: https://arxiv.org/abs/1806.05847 · HTML: https://mlsanity.com/paper/1806.05847/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Jun 2018.

## Built on by (most cited first, 8 of 8)

- [Can Large Language Models Transform Computational Social Science?](https://mlsanity.com/paper/2305.03514/) (2023)
- [Temporal Adaptation of BERT and Performance on Downstream Document Classification: Insights from Social Media](https://mlsanity.com/paper/2104.08116/) (2021)
- [LLM Agents in Interaction: Measuring Personality Consistency and Linguistic Alignment in Interacting Populations of Large Language Models](https://mlsanity.com/paper/2402.02896/) (2024)
- [Characterizing English Variation across Social Media Communities with BERT](https://mlsanity.com/paper/2102.06820/) (2021)
- [ValueScope: Unveiling Implicit Norms and Values via Return Potential Model of Social Interactions](https://mlsanity.com/paper/2407.02472/) (2024)
- [Social Meme-ing: Measuring Linguistic Variation in Memes](https://mlsanity.com/paper/2311.09130/) (2023)
- [Tracing Semantic Variation in Slang](https://mlsanity.com/paper/2210.08635/) (2022)
- [Community-Specific Slang and Entity Detection via Semantic Shift in Fine-Tuned Language Models](https://mlsanity.com/paper/2606.07522/) (2026)

## Abstract (arXiv)

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.