Data-Driven Creativity Enhancement Through Word Association

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  • Writing creative stories from a blank page is a challenging task, particularly in the modern game industry where dozens of writers can contribute to the stories and settings of a constantly evolving artificial world. We introduce a system which recommends interesting, evocative, and thematically coherent words to help creators write thematically connected stories. We combine principles from human creativity enhancement and computational creativity to build a creative assistant based on word association research. We show that careful corpus selection, filtering based on emotional sentiment, and promoting remote associations through paragraph scale segmentation can produce recommendations that promote creative goals better than alternative word association algorithms according to our creative word indicators.

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  • Copyright © 2019 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.

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  • 2019

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