Abstract
The goal of this study is two-fold: (1) to evaluate the usefulness and reliability of ChatGPT as a tool for detecting and generating nontrivial semantic categories of text, characterized by various conversational intentionalities, and (2) to build a semantic map of intentionalities and characterize its topological and geometric properties. ChatGPT 3.5 was used in this work. Results demonstrate reproducibility and reasonable accuracy. Furthermore, it was found that most intentionalities are highly correlated with each other and therefore can be expected to belong to a low-dimensional subspace on the semantic map.
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References
Ekman, P., Friesen, W.: Facial Action Coding System: A Technique for the Measurement of Facial Movement. Consulting Psychologists Press, Palo Alto (1978)
Ekman, P.: An argument for basic emotions. Cogn. Emot. 6(3–4), 169–200 (1992)
Russell, J., Mehrabian, A.: Evidence for a three-factor theory of emotions. J. Res. Pers. 11, 273–294 (1977)
Plutchik, R.: A psychoevolutionary theory of emotions. Soc. Sci. Inf. 21, 529–553 (1982)
Lövheim, H.: A new three-dimensional model for emotions and monoamine neurotransmitters. Med. Hypotheses 78(2), 341–348 (2012)
Russell, J.: Core affect and the psychological construction of emotion. Psychol. Rev. 110(1), 145–172 (2003)
Hugging Face Database. https://huggingface.co/datasets/seara/ru_go_emotions
Rzepka, R.: Emotional information retrieval for a dialogue agent. Informatica 27, 205–211 (2003)
Moors, A., Ellsworth, P.C., Scherer, K.R., Frijda, N.H.: Appraisal theories of emotion: state of the art and future development. Emot. Rev. 5(2), 119–124 (2013)
Lieto, A., Pozzato, G.L., Striani, M., Zoia, S., Damiano, R.: DEGARI 2.0: a diversity-seeking, explainable, and affective art recommender for social inclusion. Cogn. Syst. Res. 77, 1–17 (2023). https://doi.org/10.1016/j.cogsys.2022.10.001
Gadzhiev, I.M., Knyshenko, M.P., Dolenko, S.A., Samsonovich, A.V.: Inherent dimension of the affective space: analysis using electromyography and machine learning. Cogn. Syst. Res. 78, 96–105 (2023)
Samsonovich, A.V., Ascoli, G.A.: Cognitive map dimensions of the human value system extracted from natural language. Front. Artif. Intell. Appl. 157, 111–124 (2007). ISSN: 09226389
Samsonovich, A.V., De Jong, K.A., Kitsantas, A., Peters, E.E., Dabbagh, N., Kalbfleisch, M.L.: Cognitive constructor: an intelligent tutoring system based on a biologically inspired cognitive architecture (BICA). Front. Artif. Intell. Appl. 171(1), 311–325 (2008). ISSN: 09226389
Acknowledgments
This work was supported by the Russian Science Foundation Grant #22-11-00213, https://rscf.ru/en/project/22-11-00213/.
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Pavlenko, I.A., Zakirov, A.D., Yakovlev, A.N., Samsonovich, A.V. (2024). A Study of Conversational Intentionalities Expressed in Natural Language Using ChatGPT. In: Samsonovich, A.V., Liu, T. (eds) Biologically Inspired Cognitive Architectures 2023. BICA 2023. Studies in Computational Intelligence, vol 1130. Springer, Cham. https://doi.org/10.1007/978-3-031-50381-8_73
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DOI: https://doi.org/10.1007/978-3-031-50381-8_73
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