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        <title>Obtaining Reliable Human Ratings of Valence, Arousal, and Dominance for 20,000 English Words</title>
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            <namePart type="given">Yusuke</namePart>
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    <abstract>Words play a central role in language and thought. Factor analysis studies have shown that the primary dimensions of meaning are valence, arousal, and dominance (VAD). We present the NRC VAD Lexicon, which has human ratings of valence, arousal, and dominance for more than 20,000 English words. We use Best–Worst Scaling to obtain fine-grained scores and address issues of annotation consistency that plague traditional rating scale methods of annotation. We show that the ratings obtained are vastly more reliable than those in existing lexicons. We also show that there exist statistically significant differences in the shared understanding of valence, arousal, and dominance across demographic variables such as age, gender, and personality.</abstract>
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%0 Conference Proceedings
%T Obtaining Reliable Human Ratings of Valence, Arousal, and Dominance for 20,000 English Words
%A Mohammad, Saif
%Y Gurevych, Iryna
%Y Miyao, Yusuke
%S Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F mohammad-2018-obtaining
%X Words play a central role in language and thought. Factor analysis studies have shown that the primary dimensions of meaning are valence, arousal, and dominance (VAD). We present the NRC VAD Lexicon, which has human ratings of valence, arousal, and dominance for more than 20,000 English words. We use Best–Worst Scaling to obtain fine-grained scores and address issues of annotation consistency that plague traditional rating scale methods of annotation. We show that the ratings obtained are vastly more reliable than those in existing lexicons. We also show that there exist statistically significant differences in the shared understanding of valence, arousal, and dominance across demographic variables such as age, gender, and personality.
%R 10.18653/v1/P18-1017
%U https://aclanthology.org/P18-1017
%U https://doi.org/10.18653/v1/P18-1017
%P 174-184

Markdown (Informal)

[Obtaining Reliable Human Ratings of Valence, Arousal, and Dominance for 20,000 English Words](https://aclanthology.org/P18-1017) (Mohammad, ACL 2018)

• Obtaining Reliable Human Ratings of Valence, Arousal, and Dominance for 20,000 English Words (Mohammad, ACL 2018)

ACL

• Saif Mohammad. 2018. Obtaining Reliable Human Ratings of Valence, Arousal, and Dominance for 20,000 English Words. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 174–184, Melbourne, Australia. Association for Computational Linguistics.