---
title: "NRC VAD Lexicon v2 — paper by Mohammad (2025)"
description: "Valence, arousal and dominance (VAD) are widely treated as the three main, largely independent… 48 references, cited by 16 papers here."
authors: ["Saif M. Mohammad"]
year: 2025
venue: "arXiv:2503.23547"
source: "https://arxiv.org/abs/2503.23547"
doi: "10.48550/arxiv.2503.23547"
arxiv: "2503.23547"
licence: "CC BY-NC-SA 4.0 (arXiv)"
licence_url: "http://creativecommons.org/licenses/by-nc-sa/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/mohammad-2025-nrc-vad-lexicon-v2-norms/"
---
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# NRC VAD Lexicon v2: Norms for Valence, Arousal, and Dominance for over 55k English Terms

**Authors:** [Saif M. Mohammad](https://md.research.elamur.ai/free/en/authors/saif-mohammad/) · **Year:** 2025 · **Venue:** arXiv:2503.23547 · **Licence:** [CC BY-NC-SA 4.0 (arXiv)](http://creativecommons.org/licenses/by-nc-sa/4.0/)

**Links:** [Publisher's page](https://arxiv.org/abs/2503.23547) · [PDF](https://arxiv.org/pdf/2503.23547) · [DOI 10.48550/arxiv.2503.23547](https://doi.org/10.48550/arxiv.2503.23547) · [arXiv 2503.23547](https://arxiv.org/abs/2503.23547) · [OpenAlex](https://openalex.org/W4417049792)

**Citations:** 3 citations (OpenAlex, 2026-10-14) · [16](https://md.research.elamur.ai/free/en/papers/mohammad-2025-nrc-vad-lexicon-v2-norms/cited-by/) in our library, of the 149,439 papers whose bibliographies we read

## Summary
Valence, arousal and dominance (VAD) are widely treated as the three main, largely independent axes of word meaning. Dominance corresponds to "competence" in social cognition research. Existing human-rated VAD norms cover only a limited English vocabulary and almost no multi-word expressions. This paper extends the NRC VAD Lexicon from about 20k to over 55k entries. It adds roughly 25k single words and, for the first time, about 10k common phrases. New terms were taken from widely known lemmas in a word-prevalence dataset and from frequent MWEs that already have concreteness norms. Crowd workers rated each term on a seven-point scale from strongly negative to strongly positive, or the analogous poles for arousal and dominance. The questionnaires came out of several pilot rounds and include embedded check questions. Unreliable annotators were removed, and the remaining ratings were averaged into scores between -1 and 1. Split-half reliability is very high. The free resource supports sentiment and emotion analysis, psychology, the social sciences, and the evaluation of automatically induced affect lexicons.

## Key points
- NRC VAD Lexicon v2 has over 55k English terms: about 20k from v1.0, about 25k new unigrams, and about 10k MWEs.
- Split-half reliability is r = 0.99 for valence, 0.98 for arousal and 0.96 for dominance.
- The source of the new unigrams is the Prevalence dataset compiled by Brysbaert et al. (2019). A term was kept only if at least 70% of respondents knew it, and common person and city names were removed. The MWEs come from Muraki et al. (2023), which provides concreteness ratings and subtitle-corpus frequencies.
- Annotators answered on a scale from -3 to 3 and were told to choose what most English speakers would agree with. They were also told to assume the dominant sense of ambiguous words. Final scores fall in the range -1 to 1.
- Quality control used check questions with known answers that gave instant pop-up feedback. Workers whose error rate was high (about >20%) could have their work rejected, and outlier annotators were dropped before averaging.

## Interesting ideas
- Annotators were asked for the judgment they expect most speakers to share, not their personal reaction, which reduces idiosyncratic noise and some inappropriate biases.
- Check items with known answers were mixed into the task, gave instant feedback, and served as a filter for removing annotators.
- A resource's reliability was demonstrated with split-half correlation: the raters are divided into two halves and the scores each half produces are compared.
- Vocabulary was chosen by how widely people know a word and by overlap with existing norms such as concreteness, and phrases were treated as first-class entries.
- The author warns that lexicon scores reflect the predominant sense and should only support aggregate, comparative claims, never conclusions about a single utterance.

## For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

- **I1** (learn): LLM teacher prompts could request the consensus reading of a sentence or relation instead of "your opinion," which should make silver labels more stable across teachers.
- **I2** (learn): witness parsers and LLM tiers could be fed hidden items with known gold trees or frames, and any witness that fails too many could be excluded from agreement voting.
- **I3** (learn): when several witnesses produce graded scores, splitting them into halves and correlating the results gives a cheap check on whether a silver signal is consistent enough to train on.
- **I4** (world): the compiled knowledge layer could attach VAD values to lemmas and MWEs alike, for example as properties of states and events. Keying them to entries that already carry concreteness data would keep the attributes aligned.
- **I5** (frames): VAD values could serve as a weak prior for irony or attitude in a frame, for example a clash between a word's valence and the situation. That prior would always be overridden by sense-resolved, context-based evidence and not used as a per-sentence verdict.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

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🧭 Topics (2): [English](https://md.research.elamur.ai/free/en/topics/english/) · 2,263 works · [🧷 Idioms & multiword expressions](https://md.research.elamur.ai/free/en/topics/multiword-expressions/) · 217 works

## Cite

Cite as: Saif M. Mohammad. 2025. NRC VAD Lexicon v2: Norms for Valence, Arousal, and Dominance for over 55k English Terms. arXiv:2503.23547.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@misc{mohammad2025nrc,
  title = {{NRC VAD Lexicon v2: Norms for Valence, Arousal, and Dominance for over 55k English Terms}},
  author = {Saif M. Mohammad},
  year = {2025},
  doi = {10.48550/arxiv.2503.23547},
  eprint = {2503.23547},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.2503.23547}
}
```

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*Updated 1 November 2026*