The Affective Norms for Polish Short Texts (ANPST) Database Properties and Impact of Participants’ Population and Sex on Affective Ratings

نویسنده

  • Kamil K. Imbir
چکیده

The Affective Norms for Polish Short Texts (ANPST) dataset (Imbir, 2016d) is a list of 718 affective sentence stimuli with known affective properties with respect to subjectively perceived valence, arousal, dominance, origin, subjective significance, and source. This article examines the reliability of the ANPST and the impact of population type and sex on affective ratings. The ANPST dataset was introduced to provide a recognized method of eliciting affective states with linguistic stimuli more complex than single words and that included contextual information and thus are less ambiguous in interpretation than single word. Analysis of the properties of the ANPST dataset showed that norms collected are reliable in terms of split-half estimation and that the distributions of ratings are similar to those obtained in other affective norms studies. The pattern of correlations was the same as that found in analysis of an affective norms dataset for words based on the same six variables. Female psychology students' valence ratings were also more polarized than those of their female student peers studying other subjects, but arousal ratings were only higher for negative words. Differences also appeared for all other measured dimensions. Women's valence ratings were found to be more polarized and arousal ratings were higher than those made by men, and differences were also present for dominance, origin, and subjective significance. The ANPST is the first Polish language list of sentence stimuli and could easily be adapted for other languages and cultures.

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عنوان ژورنال:

دوره 8  شماره 

صفحات  -

تاریخ انتشار 2017