Semantic Apparatus – Automating creativity assessment with SemDis: An open platform for computing semantic distance

Cited by Lee Sonogan

How Automation Leads to Creative Confidence

Abstract by Roger E. Beaty &Dan R. Johnson 

Creativity research requires assessing the quality of ideas and products. In practice, conducting creativity research often involves asking several human raters to judge participants’ responses to creativity tasks, such as judging the novelty of ideas from the alternate uses task (AUT). Although such subjective scoring methods have proved useful, they have two inherent limitations—labor cost (raters typically code thousands of responses) and subjectivity (raters vary on their perceptions and preferences)—raising classic psychometric threats to reliability and validity. We sought to address the limitations of subjective scoring by capitalizing on recent developments in automated scoring of verbal creativity via semantic distance, a computational method that uses natural language processing to quantify the semantic relatedness of texts. In five studies, we compare the top performing semantic models (e.g., GloVe, continuous bag of words) previously shown to have the highest correspondence to human relatedness judgements. We assessed these semantic models in relation to human creativity ratings from a canonical verbal creativity task (AUT; Studies 1–3) and novelty/creativity ratings from two word association tasks (Studies 4–5). We find that a latent semantic distance factor—comprised of the common variance from five semantic models—reliably and strongly predicts human creativity and novelty ratings across a range of creativity tasks. We also replicate an established experimental effect in the creativity literature (i.e., the serial order effect) and show that semantic distance correlates with other creativity measures, demonstrating convergent validity. We provide an open platform to efficiently compute semantic distance, including tutorials and documentation (https://osf.io/gz4fc/).

Publicaiton: Behavior Research Methods (Peer-Reviewed Journal)

Pub Date: 31 Aug, 2020 Doi: https://doi.org/10.3758/s13428-020-01453-w

Keywords: Assessment, Creativity, Divergent thinking, Semantic distance, Word association

https://link.springer.com/article/10.3758/s13428-020-01453-w#citeas (Plenty more sections and references in this research article)

https://www.patreon.com/GROOVYGORDS

https://entertainmentcultureonline.com/

https://ungroovygords.com/

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