We Need to Measure Data Diversity in NLP -- Better and Broader

Dong Nguyen, Esther Ploeger
5/26/2025
cs.CLcs.AI

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Abstract

Although diversity in NLP datasets has received growing attention, the question of how to measure it remains largely underexplored. This opinion paper examines the conceptual and methodological challenges of measuring data diversity and argues that interdisciplinary perspectives are essential for developing more fine-grained and valid measures.

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Cite this paper

@article{nguyen2025need,
  title  = {We Need to Measure Data Diversity in NLP -- Better and Broader},
  author = {Dong Nguyen and Esther Ploeger},
  year   = {2025},
  eprint = {2505.20264},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2505.20264v2}
}

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