# Language, Place, and Social Media: Geographic Dialect Alignment in New Zealand

arXiv: https://arxiv.org/abs/2604.15744 · HTML: https://mlsanity.com/paper/2604.15744/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 370 references that are in the map.
- First posted on arXiv 17 Apr 2026.

## Builds on (most cited first, 1 of 1)

- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)

## Built on by (most cited first, 1 of 1)

- [Wiktionary as a Crowdsourced Lexicon for English Dialects](https://mlsanity.com/paper/2608.15641/) (2026)

## Abstract (arXiv)

This thesis investigates geographic dialect alignment in place-informed social media communities, focussing on New Zealand-related Reddit communities. By integrating qualitative analyses of user perceptions with computational methods, the study examines how language use reflects place identity and patterns of language variation and change based on user-informed lexical, morphosyntactic, and semantic variables. The findings show that users generally associate language with place, and place-related communities form a contiguous speech community, though alignment between geographic dialect communities and place-related communities remains complex. Advanced language modelling, including static and diachronic Word2Vec language embeddings, revealed semantic variation across place-based communities and meaningful semantic shifts within New Zealand English. The research involved the creation of a corpus containing 4.26 billion unprocessed words, which offers a valuable resource for future study. Overall, the results highlight the potential of social media as a natural laboratory for sociolinguistic inquiry.