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Intuitive (in)coherence judgments are guided by processing fluency, mood and affect.
Joanna Sweklej1, Robert Balas, Grzegorz Pochwatko
1Department of Psychology, Warsaw School of Social Sciences and Humanities, 19/31 Chodakowska St, 03-815, Warsaw, Poland, jsweklej@swps.edu.pl.
Processing fluency, how easily information is processed, can signal semantic incoherence, not just coherence. Fluency variations, not fluency itself, influence intuitive judgments of semantic meaning.
Area of Science:
- Cognitive Psychology
- Linguistics
- Neuroscience
Background:
- Current theories link processing fluency to positive affect and successful semantic coherence judgments.
- The role of processing fluency in identifying semantic incoherence remains underexplored.
- Investigating fluency's dual role in semantic assessment is crucial for understanding intuitive judgments.
Purpose of the Study:
- To determine if processing fluency can also indicate semantic incoherence.
- To examine the influence of affective valence and mood on these judgments.
- To test the hypothesis that fluency variations, not absolute fluency, drive semantic judgments.
Main Methods:
- Two studies were conducted using a novel paradigm where participants identified incoherent items among coherent words.
- Study 1 manipulated the affective valence of solution words.
- Study 2 examined the moderating effect of participant mood on incoherence judgments.
Main Results:
- Participants accurately identified incoherent items, demonstrating fluency's potential to signal incoherence.
- Affective valence of solutions modulated incoherence detection.
- Participant mood influenced incoherence judgments independently of solution valence, confirming fluency variations are key.
Conclusions:
- Processing fluency variations, not just the level of fluency, are critical drivers of intuitive semantic coherence judgments.
- These findings challenge existing models by showing fluency can signal both coherence and incoherence.
- The study highlights the complex interplay between fluency, affect, and mood in semantic processing.
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