Ratings of valence, arousal, happiness, anger, fear, sadness, disgust, and surprise for 24,000 Dutch words
Abstract Emotion is a fundamental aspect of human life and therefore is critically encoded in language. To facilitate research into the encoding of emotion in language and how emotion associations affect language processing, we present a new set of emotion norms for over 24,000 Dutch words. The emotion norms include ratings of two key dimensions of emotion: valence and arousal, as well as ratings on discrete emotion categories: happiness, anger, fear, sadness, disgust, and surprise. We show that emotional information can predict word processing, such that responses to positive words are facili... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2023 |
Reihe/Periodikum: | Behavior Research Methods ; ISSN 1554-3528 |
Verlag/Hrsg.: |
Springer Science and Business Media LLC
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Schlagwörter: | General Psychology / Psychology (miscellaneous) / Arts and Humanities (miscellaneous) / Developmental and Educational Psychology / Experimental and Cognitive Psychology |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-27079428 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | http://dx.doi.org/10.3758/s13428-023-02239-6 |
Abstract Emotion is a fundamental aspect of human life and therefore is critically encoded in language. To facilitate research into the encoding of emotion in language and how emotion associations affect language processing, we present a new set of emotion norms for over 24,000 Dutch words. The emotion norms include ratings of two key dimensions of emotion: valence and arousal, as well as ratings on discrete emotion categories: happiness, anger, fear, sadness, disgust, and surprise. We show that emotional information can predict word processing, such that responses to positive words are facilitated in contrast to neutral and negative words. We also demonstrate how the ratings of emotion are related to personality characteristics. The data are available via the Open Science Framework ( https://osf.io/9htuv/ ) and serve as a valuable resource for research into emotion as well as in applied settings such as healthcare and digital communication.