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

<p><strong>Context and relevance. </strong>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. <strong>Objective:</strong> 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. <strong>Hypothesis.</strong> Dialogue between a human and a neural network is a social act and is structurally similar to dialogue between humans. <strong>Methods and materials. </strong>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. <strong>Results.</strong> 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.</p>

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Publication Details

Journal
Experimental Psychology (Russia)
Published
2025-06-30
DOI
https://doi.org/10.17759/exppsy.2025180206
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
0.00

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article

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

V.V. Selivanov, A.A. Shamshev
Experimental Psychology (Russia)
Topic Modeling
article

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

V.V. Selivanov, A.A. Shamshev
article en

Abstract

<p><strong>Context and relevance. </strong>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. <strong>Objective:</strong> 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. <strong>Hypothesis.</strong> Dialogue between a human and a neural network is a social act and is structurally similar to dialogue between humans. <strong>Methods and materials. </strong>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. <strong>Results.</strong> 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.</p>

Experimental Psychology (Russia)Vol. 18(2)
Moscow State University of Psychology & Education (RU)
Russian Science Foundation
Openalex Percentile: Top 89%
Topic Modeling
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