Valence, Arousal and Concreteness Mediate Word Association

  1. Francisco Buades-Sitjar 1
  2. Clara Planchuelo 1
  3. Jon Andoni Duñabeitia 1
  1. 1 Universidad Nebrija
    info
    Universidad Nebrija

    Madrid, España

    ROR https://ror.org/03tzyrt94

    Geographic location of the organization Universidad Nebrija
Journal:
Psicothema

ISSN: 0214-9915,  1886-144X

Year of publication: 2021

Volume: 33

Issue: 4

Pages: 602-609

Type: Article

DOI: 10.7334/PSICOTHEMA2020.484 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: Psicothema

Sustainable development goals

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SDG classification obtained using Aurora SDG artificial intelligence model.

Abstract

Background: Given the impact of lexical properties such as valence, arousal, and concreteness in language processing, recent computational methods have been designed to extrapolate these values from different sources, such as word co-occurrence or word association corpora. These methods have been proven to be particularly successful approaches to extract lexical features from word association data. Consequently, valence, arousal and concreteness seem to be represented in word association, and we hypothesize that they might in fact be critical mediators in the process. Method: To test our hypothesis, we paired the cue and associate words from three databases in three different languages with their valence, arousal and concreteness values. We then conducted linear regression analyses to see if an associate’s score in each dimension could be predicted by the scores of its cue word. Results: The analyses showed that the score of the cue words in each of the three dimensions was a strong predictor of the scores of their associates in the same dimension. Furthermore, words that were more strongly associated tended to have more similar scores. Conclusions: We showed that across different languages, word association is mediated and can be predicted by concreteness, arousal and valence.

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Funding information

This study was partially supported by grants RED2018-102615-T and PGC2018-097145-BI00 from the Spanish Government, and H2019/HUM-5705 from the Comunidad de Madrid.

Funders

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