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4. Flexible semantic network structure supports the production of creative metaphor

   https://doi.org/10.1080/10400419.2021.1879508  

   Li, Yangping; Kenett, Yoed N.; Hu, Weiping; Beaty, Roger E. (January 2021, Creativity Research Journal)

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   Metaphors are a common way to express creative language, yet the cognitive basis of figurative language production remains poorly understood. Previous studies found that higher creative individuals can better comprehend novel metaphors, potentially due to a more flexible semantic memory network structure conducive to remote conceptual combination. The present study extends this domain to creative metaphor production and examined whether the ability to produce creative metaphors is related to variation in the structure of semantic memory. Participants completed a creative metaphor production task and two verbal fluency tasks. They were divided into two equal groups based on their creative metaphor production score. The semantic networks of these two groups were estimated and analyzed based on their verbal fluency responses using a computational network science approach. Results revealed that the semantic networks of high-metaphor producing individuals were more flexible, clustered, and less rigid than that of the low-metaphor producing individuals. Importantly, these results replicated across both semantic categories. The findings provide the first evidence that a flexible, clustered, and less rigid semantic memory structure relates to people’s ability to produce figurative language, extending the growing literature on the role of semantic networks in creativity to the domain of metaphor production. 

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5. Exploring How Generating Metaphor Via Insight Versus Analysis Affects Metaphor Quality and Learning Outcomes

   https://doi.org/10.1111/cogs.13488  

   Yu, Yuhua; Krebs, Lindsay; Beeman, Mark; Lai, Vicky T (August 2024, Cognitive Science)

   Abstract Metaphor generation is both a creative act and a means of learning. When learning a new concept, people often create a metaphor to connect the new concept to existing knowledge. Does the manner in which people generate a metaphor, via sudden insight (Aha! moment) or deliberate analysis, influence the quality of generation and subsequent learning outcomes? According to some research, deliberate processing enhances knowledge retention; hence, generation via analysis likely leads to better concept learning. However, other research has shown that solutions generated via insight are better remembered. In the current study, participants were presented with science concepts and descriptions, then generated metaphors for the concepts. They also indicated how they generated each metaphor and rated their metaphor for novelty and aptness. We assessed participants’ learning outcomes with a memory test and evaluated the creative quality of the metaphors based on self‐ and crowd‐sourced ratings. Consistent with the deliberate processing benefit, participants became more familiar with the target science concept if they previously generated a metaphor for the concept via analysis compared to via insight. We also found that metaphors generated via analysis did not differ from metaphors generated via insight in quality (aptness or novelty) nor in how well they were remembered. However, participants’ self‐evaluations of metaphors generated via insight showed more agreement with independent raters, suggesting the role of insight in modulating the creative ideation process. These preliminary findings have implications for understanding the nature of insight during idea generation and its impact on learning. 

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