| Title |
Moved by words: Affective ratings for a set of 2,266 Spanish words in five discrete emotion categories
|
|---|---|
| Published in |
Behavior Research Methods, July 2016
|
| DOI | 10.3758/s13428-016-0768-3 |
| Pubmed ID | |
| Authors |
Pilar Ferré, Marc Guasch, Natalia Martínez-García, Isabel Fraga, José Antonio Hinojosa |
| Abstract |
The two main theoretical accounts of the human affective space are the dimensional perspective and the discrete-emotion approach. In recent years, several affective norms have been developed from a dimensional perspective, including ratings for valence and arousal. In contrast, the number of published datasets relying on the discrete-emotion approach is much lower. There is a need to fill this gap, considering that discrete emotions have an effect on word processing above and beyond those of valence and arousal. In the present study, we present ratings from 1,380 participants for a set of 2,266 Spanish words in five discrete emotion categories: happiness, anger, fear, disgust, and sadness. This will be the largest dataset published to date containing ratings for discrete emotions. We also present, for the first time, a fine-grained analysis of the distribution of words into the five emotion categories. This analysis reveals that happiness words are the most consistently related to a single, discrete emotion category. In contrast, there is a tendency for many negative words to belong to more than one discrete emotion. The only exception is disgust words, which overlap least with the other negative emotions. Normative valence and arousal data already exist for all of the words included in this corpus. Thus, the present database will allow researchers to design studies to contrast the predictions of the two most influential theoretical perspectives in this field. These studies will undoubtedly contribute to a deeper understanding of the effects of emotion on word processing. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Unknown | 53 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 17% |
| Professor | 6 | 11% |
| Student > Bachelor | 6 | 11% |
| Student > Doctoral Student | 5 | 9% |
| Researcher | 5 | 9% |
| Other | 15 | 28% |
| Unknown | 8 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 17 | 31% |
| Linguistics | 10 | 19% |
| Neuroscience | 5 | 9% |
| Social Sciences | 3 | 6% |
| Computer Science | 1 | 2% |
| Other | 5 | 9% |
| Unknown | 13 | 24% |
Attention Score in Context
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#16,720,137
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Outputs from Behavior Research Methods
#1,538
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Outputs of similar age from Behavior Research Methods
#27
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