Study Operationalization Context
Bossomaier, Terry, Mike Harré, Anthony Knittel, and Allan Snyder (2009), “A semantic network approach to the creativity quotient (CQ),” Creativity Research Journal, 21(1), 64-71.
Semantic similarity using Wordnet
Ideation fluency and flexibility
Forster, Eve A., and Kevin N. Dunbar (2009), “Creativity Evaluation Through Latent Semantic Analysis,” Proceedings of the Annual Conference of the Cognitive Science Society, 602-607.
LSA Creativity in Uses of Objects
Task; Divergent Thinking Tests
Walter, Thomas P., and Andrea Back (2013), “A text mining approach to evaluate submissions to
crowdsourcing contests,” 46th Hawaii International Conference on System Sciences, IEEE, 3109-3118.
TF-IDF, Clustering Evaluation of quality of submission on online crowdsourcing platform
Uzzi, B., S. Mukherjee, M. Stringer and B. Jones. 2013. “Atypical Combinations and Scientific Impact.” Science 342(6157):468–472.
Rareness of its pairwise combinations of references
Novelty and impact of academic research
Harbinson, J. Isaiah, and Henk Haarman (2014), “Automated Scoring of Originality Using Semantic Representations,” Proceedings of the Annual Meeting of the Cognitive Science Society, 36 (6), 1069-7977
LSA, PMI Evaluation of creativity in
tests of divergent thinking
Kaplan, Sarah, and Keyvan Vakili (2015), “The
Double-edged Sword of Recombination in Breakthrough Innovation,” Strategic Management Journal, 36(10), 1435-1457.
LDA Evaluation of novel ideas in
patents
Chan, Joel, and Christian D. Schunn
(2015), “The importance of iteration in creative conceptual combination,” Cognition, 145, 104-115.
LDA Novelty of ideas
Lee, You-Na, John P. Walsh, and Jian Wang (2015), “Creativity in scientific teams: Unpacking novelty and impact,” Research Policy, 44(3), 684-697.
Rareness of its pairwise combinations of references
Novelty and impact of academic research
Dasgupta, Tirthankar, and Lipika Dey (2016), “Automatic Scoring for Innovativeness of Textual Ideas,” The Workshops of the Thirtieth AAAI Conference on Artificial Intelligence Knowledge Extraction from Text: Technical Report WS-16-10
Entropy, Cosine Similarity, KL Divergence
Novelty of texts
Omari, Adi, David Carmel, Oleg Rokhlenko, and Idan Szpektor (2016), “Novelty based ranking of human answers for community questions,” Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 215-224, ACM. TF-IDF, Word2Vec, Explicit Semantic Analysis (ESA) Ranking of answers on community-based question answering (CQA) sites based on novelty.
Cvitanic, Toni, Bumsoo Lee, Hyeon Ik Song, Katherine Fu, and David Rosen (2016), “LDA v. LSA: A
comparison of two computational text analysis tools for the functional categorization of patents,” International Conference on Case-Based Reasoning.
Carayol, N., A. Lahatte, and O. Llopis (2018), “The right job and the job right: Novelty, impact and journal stratification in science,” Retrieved from:
conference.druid.dk/acc˙papers/.
Pair-wise combination of keyword
Novelty of academic papers
Chan, Joel, Pao Siangliulue, Denisa Qori McDonald, Ruixue Liu, Reza Moradinezhad, Safa Aman, Erin T. Solovey, Krzysztof Z. Gajos, and Steven P. Dow (2017), “Semantically Far Inspirations Considered Harmful?: Accounting for Cognitive States in Collaborative Ideation,” In Proceedings of the 2017 ACM SIGCHI Conference on Creativity and Cognition, 93-105. ACM.
GloVe Role of creative ideas in the
production of ideas
Christensen, Kasper, Sladjana Nørskov, Lars Frederiksen, and Joachim Scholderer (2017), “In search of new product ideas: Identifying ideas in online communities by machine learning and text mining,” Creativity and Innovation Management, 26(1), 17-30.
Support Vector Machine, PLS
Detection and classification of ideas
R. W. Hass, R. W. (2017), “Tracking the dynamics of divergent thinking via semantic distance: Analytic methods and theoretical implications,” Memory and Cognition, 45(2), 233-244.
LSA Tracking dynamics of
divergent thinking
Heinen, D. J. P., & Johnson, D. R. (2018), “Semantic distance: An automated measure of creativity that is novel and appropriate,” Psychology of Aesthetics, Creativity, and the Arts, 12(2), 144-156
Semantic Distance Evaluation of novelty and appropriateness
Hoornaert, Steven, Michel Ballings, Edward C. Malthouse, and Dirk Van den Poel (2017), “Identifying new product ideas: waiting for the wisdom of the crowd or screening ideas in real time,” Journal of Product Innovation Management, 34(5), 580-597.
LSA Predicting implement ability
of crowdsourced ideas
Skalicky, Stephen, Scott A. Crossley, Danielle S. McNamara, and Kasia Muldner (2017) “Identifying creativity during problem solving using linguistic features,” Creativity Research Journal, 29(4), 343-353.
Linguistic Analysis; Linear Mixed Effects Analysis
Creativity in collaborative divergent thinking tasks.
Toubia, Olivier, and Oded Netzer (2017), “Idea Generation, Creativity, and Prototypicality,” Marketing Science, 36(1), 1-20.
Semantic Network; Kolmogorov-Smrirnov Statistic
Creativity of ideas
Amplayo, Reinald Kim, SuLyn Hong, and Min Song. "Network-based approach to detect novelty of scholarly literature." Information Sciences, 422, 542-557.
TF-IDF; SVM; Graph; neural network
Novelty of academic papers
Ahmed, Faez, Mark Fuge, Sam Hunter, and Scarlett Miller (2018), “Unpacking subjective creativity ratings: Using embeddings to explain and measure idea
novelty,” ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference.
Embedding Novelty of ideas
Ahmed, Faez, and Mark Fuge (2018), “Creative exploration using topic-based bisociative networks,” Design Sciences, 4(12), 1-30.
Topic Modeling Novelty of ideas
Berger, Jonah, and Grant Packard
(2018), “Are atypical things more popular?” Psychological Science, 29(7), 1178-1184.
Fontana, Magda, Martina Iori, Fabio Montobbio, and Roberta Sinatra (2018), “A bridge over troubled water: Interdisciplinarity, Novelty, and Impact,” No. dipe0002. Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
Rareness of its pairwise combinations of references
Novelty of academic research
Mei, Mei, Xinyu Guo, Belinda C. Williams, Simona Doboli, Jared B. Kenworthy, Paul B. Paulus, and Ali A. Minai (2018), “Using Semantic Clustering And Autoencoders For Detecting Novelty In Corpora Of Short Texts,” 2018 International Joint Conference on Neural Networks (IJCNN), IEEE, 1-8.
LDA, Autoencoders Novelty of ideas
Dellermann, Dominik, Nikolaus Lipusch, and Mahei Li (2018), “Combining Humans and Machine Learning: A Novel Approach for Evaluating Crowdsourcing Contributions in Idea Contests,” (2018).
Topic modeling, Machine learning
Filtering of crowdsourced ideas
Parde, Natalie, and Rodney D. Nielsen (2018), “Exploring the terrain of metaphor novelty: A regression-based approach for automatically scoring metaphors,” Thirty-Second AAAI Conference on Artificial Intelligence.
Word Embedding, TF- IDF, SynSet,
Psycholinguistics
Scoring novelty of metaphors
Toubia, Olivier (2019), “A Poisson Factorization Topic Model for the Study of Creative Documents (and Their Summaries),” Available at SSRN 3334028.
Poisson Factorization Novelty of creative content
Wang, Kai, Boxiang Dong, and Junjie Ma (2019), “Towards Computational Assessment of Idea Novelty,” Proceedings of the 52nd Hawaii International
Conference on System Sciences.