I really enjoy computational modelling and quantitative approaches. Sometimes however it’s easy to let the algorithms get away from you, so I think that it is important to be very careful about any hint of causality in this line of research. My most recent 2020 paper in Dialogue and Discourse presents a method which I think strikes a fair balance between data mining and hypothesis testing. I am keen to talk with you about these papers and what the results might “mean”!
Skalicky, S., Duran, N., & Crossley, S. A. (2020). Please, please, just tell me: The linguistic features of humorous deception. Dialogue and Discourse (11)2, 128-149. Open Access
Skalicky, S., Crossley, S.A., McNamara, D.S., & Muldner, K. (2017). Identifying creativity during problem solving using linguistic features. Creativity Research Journal, 29(4), 343-353. Journal Site
Skalicky, S., Berger, C. M., Crossley, S. A., & McNamara, D. S. (2016). Linguistic features of humor in academic writing. Advances in Language and Literary Studies, 7(3), 248-259. Open Access
Skalicky, S., Crossley, S.A., McNamara, D.S., & Muldner, K. (2019). Measuring creative ability in spoken bilingual text: The role of language proficiency and linguistic features. In Proceedings of the 41st Annual Meeting of the Cognitive Science Society (pp. 1056-1062). Montreal, QB: Cognitive Science Society. Open Access
Skalicky, S. & Crossley, S.A. (2018). Linguistic features of sarcasm and metaphor production quality. In Proceedings of the Workshop on Figurative Language Processing at the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT), 7-16. Open Access
Skalicky, S., Crossley, S.A., McNamara, D.S., & Muldner, K. (2017). Automatically identifying humorous and persuasive language produced during a creative problem-solving task. In Proceedings of the Thirtieth International Florida Artificial Intelligence Research Society Conference, 282-287. Open Access