Structural differences of dialogues between humans and dialogues between humans and neural networks

 
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Abstract

Context and relevance. The rapid development of generative neural networks, beginning in 2022, has created a situation where dialogue with a character previously considered fictional and inaccessible for communication becomes possible. Potentially, the development of these systems will allow humans to gain experience comparable to that of social communication. The existence of such experience raises the question of where the boundary lies between social and parasocial relationships. Objective: to determine the presence or absence of differences between a human's dialogue with a neural network and a human's dialogue with another human. Hypothesis. Dialogue between a human and a neural network is a social act and is structurally similar to dialogue between humans. Methods and materials. The study conducts a comparative analysis of dialogues between humans and humans, and between humans and the ChatGPT 3.5 neural network, from the perspective of the psycholinguistic structure of speech. Materials from an empirical study involving a sample of students and graduate students from various Moscow universities are provided. The study created a virtual environment for oral communication between a human and a neural network; the dialogues were recorded, transcribed (converted into text format without additional processing), and compared with human-to-human dialogues, which were also recorded and transcribed. The study analyzed eighty adjacency pairs—pairs of adjacent utterances, pairs of statements by different participants located in immediate proximity to each other during interaction, taken from six dialogues. Human-to-human dialogues were conducted among respondents aged 20 to 22, of whom two were female and two were male. Human-to-neural network dialogues were conducted among respondents aged 20 to 28, of whom two were male and four were female. The study employed the method of conversation analysis, focusing on the types of difficulties respondents experienced in dialogue. Additionally, the length of utterances was examined to compare speech structure. Results. The obtained results indicate significant differences in the structure of dialogue between a human and ChatGPT 3.5 compared to dialogue between two humans, in terms of the distribution of utterance lengths in words and the types of communicative difficulties in dialogue.

General Information

Keywords: artificial intelligence, ChatGPT, convergent analysis, dialog, communication, communication psychology

Journal rubric: Psychology of Digital Reality

OpenAlex citations: 0

OpenAlex topics: Topic Modeling, Action Observation and Synchronization, Cognitive Science and Education Research

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Number of citations: 0

Topics

Topic Modeling

This cluster of papers covers a wide range of advancements in natural language processing, including neural network architectures, word representation models, machine translation techniques, text classification algorithms, semantic similarity measures, named entity recognition methods, pretrained language models, sequence-to-sequence learning approaches, topic modeling strategies, and information retrieval systems.

Number of works: 161767  |  Total number of citations: 2623161

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Action Observation and Synchronization

This cluster of papers explores the concept of embodied cognition, focusing on the role of the mirror neuron system, neural mechanisms underlying action observation, social cognition, language comprehension, and interpersonal synchrony. The research delves into how the motor system and embodiment influence social interaction and understanding of intentions.

Number of works: 45109  |  Total number of citations: 1117908

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Cognitive Science and Education Research

This cluster of papers explores the intersection of physics, cognitive science, and philosophy to understand the nature of mind, cognition, consciousness, language, emotions, and symbolic culture. It delves into topics such as neural networks, music, aesthetic emotions, philosophy of engineering, and the physics of selfhood.

Number of works: 33198  |  Total number of citations: 358717

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Work details in OpenAlex

Article type: scientific article

DOI: https://doi.org/10.17759/exppsy.2025180206

Funding. The research is conducted with financial support from the Russian Science Foundation, project No. 25-18-00885 “Real and Virtual Intellectual Events in Solving Complex Problems”.

Received 03.06.2025

Revised 24.06.2025

Accepted

Published

For citation: Shamshev, A.A., Selivanov, V.V. (2025). Structural differences of dialogues between humans and dialogues between humans and neural networks. Experimental Psychology (Russia), 18(2), 104–114. (In Russ.). https://doi.org/10.17759/exppsy.2025180206

© Shamshev A.A., Selivanov V.V., 2025

License: CC BY-NC 4.0

References

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Appendix

Appendix

Appendix. Dialogues with the neural network ChatGPT 3.5 (In Russ.).

Information About the Authors

Andrei A. Shamshev, Student of the Institute of Experimental Psychology, Moscow State University of Psychology and Education, Moscow, Russian Federation, ORCID: https://orcid.org/0009-0002-2161-6560, e-mail: shamshev-andrei@ya.ru

Vladimir V. Selivanov, Doctor of Psychology, Professor, Professor, Head of the Department of General Psychology, Moscow State University of Psychology and Education, Head of the Chair of General Psychology, Smolensk State University, Smolensk, Russian Federation, ORCID: https://orcid.org/0000-0002-8386-591X, e-mail: vvsel@list.ru

Contribution of the authors

Andrey A. Shamshev — research concept; theoretical background compilation; experimental environment preparation; experimental data collection and analysis; research results visualization; data interpretation; writing text.

Vladimir V. Selivanov — scientific supervision; verification of scientific novelty and theoretical background relevance; research process oversight; writing text, final editing.

Both authors participated in discussing the results and approved the final manuscript text.

Conflict of interest

The authors declare no conflict of interest.

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