Analysis of ChatGPT-generated texts on Taiwan’s disputed status

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Abstract

Artificial intelligence technologies are gradually becoming more common in modern society. The political sphere is not left aside, where these technologies are also being considered and are beginning to be applied. The purpose of this research is to identify the features of the presentation of texts generated by one of the most popular online services, neural network ChatGPT, for key text queries associated with two approaches to the issue of the political status of Taiwan: considering Taiwan as part of the Chinese People’s Republic or as an independent and sovereign territorial entity. Quantitative content analysis and frame analysis are used as basic methods. The information array of data consists of the results obtained from two text queries: “Taiwan as an independent entity in...” and “Taiwan as part of China in...” for four time points (2010, 2015, 2020 and 2023), selected based on the principle of equal distance and the period of the study (2023). The total number of words for analysis was 1402. The study found that for a text query directly related to the independent and sovereign political status of Taiwan, artificial intelligence generates larger texts than for a text query related to the statement of its territorial affiliation with the PRC. From the point of view of symbolic words/expressions-markers, indicating a particular approach to the specified political issues, the content generated by artificial intelligence revealed the absolute advantage of words/expressions-markers, symbolically reflecting the idea of the independent and sovereign political status of Taiwan, and not its territorial affiliation with the PRC. Possible reasons for such a distribution of the frequency of occurrence of the specified words/expressions of markers in the information array are indicated. The presence of at least three common frames in the entire information array has been established, which are designated as follows: “Independent entity”, “The part of China” and “Tensions and confrontation”.

About the authors

Aleksandr Yu. Petukhov

Lomonosov Moscow State University

Email: lectorr@yandex.ru
ORCID iD: 0000-0002-7412-5397

Сandidate of Political Sciences, Associate Professor, Head of the Laboratory of Mathematical Methods of Political Analysis and Forecasting

1 Leninskie Gory, Moscow, 119991, Russian Federation

Dmitriy I. Kaminchenko

Lobachevsky State University of Nizhny Novgorod

Author for correspondence.
Email: dmitkam@inbox.ru
ORCID iD: 0000-0002-3193-3423

Candidate of Political Sciences, Associate Professor at the Department of Political Science, Institute of International Relations and World History

23 Gagarina Prospect, Nizhny Novgorod, 603022, Russian Federation

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Copyright (c) 2024 Petukhov A.Y., Kaminchenko D.I.

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