Modelling creativity: identifying key components through a corpus-based approach

Jordanous, Anna and Keller, Bill (2016) Modelling creativity: identifying key components through a corpus-based approach. PLoS ONE, 11 (10). pp. 1-27. ISSN 1932-6203

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Abstract

Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept. Using techniques from the field of statistical natural language processing, we identify a collection of fourteen key components of creativity through an analysis of a corpus of academic papers on the topic. Words are identified which appear significantly often in connection with discussions of the concept. Using a measure of lexical similarity to help cluster these words, a number of distinct themes emerge, which collectively contribute to a comprehensive and multi-perspective model of creativity. The components provide an ontology of creativity: a set of building blocks which can be used to model creative practice in a variety of domains. The components have been employed in two case studies to evaluate the creativity of computational systems and have proven useful in articulating achievements of this work and directions for further research.

Item Type: Article
Keywords: Creativity, Language, Semantics
Schools and Departments: School of Engineering and Informatics > Informatics
Research Centres and Groups: Data Science Research Group
Subjects: P Language and Literature > P Philology. Linguistics > P0098 Computational linguistics. Natural language processing
Q Science > QA Mathematics > QA0075 Electronic computers. Computer science
Depositing User: Bill Keller
Date Deposited: 19 Apr 2017 08:04
Last Modified: 19 Apr 2017 08:15
URI: http://sro.sussex.ac.uk/id/eprint/67410

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