Correlation between affective word's dimensions and lexico-semantic features in Persian-speaking students

Message:
Abstract:
Introduction
Emotion have an important role in brain`s cognitive functions and information processing such as visual words` recognition rate. Emotion is considered to have two different dimensions: Valence and Arousal. Only a few studies have considered both of these aspects and it is not yet clear if they are either separated aspects or have correlation with each other. On the other hand, word`s recognition speed is influenced by some lexico-semantic features too. Finding correlation between affective dimensions and lexico-semantic features is important in studying the distinctiveness of affective dimensions.
Materials And Methods
100 university students scored to 300 words in the questionnaire related to affective dimensions and lexico-semantic features, based on Likert rating scale. Then data correlation was studied by linear and quadratic regression tests.
Results
There was a strong positive correlation between valence and arousal as valence was increased by arousal increments. Negative words were significantly more arousal than the positive ones. There was a moderate positive correlation between the valence and the familiarity of the words. Also, there was an equal week correlation between the imaginability and valence and the imaginability and arousal, which means words with higher arousal or valence, are more imaginable.
Conclusion
In spite of significant correlation between the arousal and valence, they are distinct variables; since the sense of arousal was different for positive and negative words, while, each emotional dimension correlated with different lexico-semantic feature. This independency should be considered in future studies. The Persian affective words` list, which was used in this study and rated for both lexico-semantic and emotional dimensions, could also be used as a primary tool in future studies
Language:
Persian
Published:
Pages:
320 to 328
magiran.com/p1383979  
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