A Comparison of Rhetorical Move Analysis by GPT-4 and Humans in Abstracts of Scopus-Indexed Tourism Research Articles

International Linguistics Research Pub Date : 2024-06-05 DOI:10.30560/ilr.v7n2p1

Hui Geng, V. Nimehchisalem, Mohsen Zargar, J. Mukundan

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引用次数: 0

Abstract

AI advancements have made ChatGPT a remarkable and versatile tool in education and linguistics, showcasing its potential to mimic human conversation and comprehend language. Scholars are intrigued by ChatGPT’s text data handling, yet its application in rhetorical move analysis remains largely unexplored. Therefore, the objective of this study is to investigate the ability of GPT-4 in the identification of rhetorical moves employed in the abstracts of tourism research articles indexed in Scopus. The essentiality of moves was also reported. Additionally, this research seeks to compare the accuracy of GPT-4’s analysis with that of humans. Adopting Hyland’s (2000) five-move model, the results indicated that GPT-4 analyzes moves more quickly but less accurately than human experts, and the four principal types of errors committed by GPT-4 include redundancy/over-count, unmatched categorization, incorrect sequence, and vague identification. The findings also revealed that Move 2 (Purpose) and Move 4 (Findings) are obligatory with a 100% essentiality rate through both GPT-4 and human analysis. Differences arise in certain steps of Move 1 (Introduction), Move 3 (Methods), and Move 5 (Conclusion), where GPT-4 often sees higher essentiality rates. This study shed light on the testament to AI’s current capabilities in move analysis in academic discourse.

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通过 GPT-4 和人类对 Scopus 索引的旅游研究文章摘要中的修辞动作分析进行比较

人工智能的进步使 ChatGPT 在教育和语言学领域成为一个出色的多功能工具，展示了它在模仿人类对话和理解语言方面的潜力。学者们对 ChatGPT 的文本数据处理能力非常感兴趣，但其在修辞动作分析中的应用却仍未得到广泛探索。因此，本研究旨在探讨 GPT-4 在识别 Scopus 所收录的旅游研究文章摘要中使用的修辞手法方面的能力。同时还报告了修辞动作的本质。此外，本研究还试图比较 GPT-4 与人类分析的准确性。采用 Hyland（2000 年）的五招模型，结果表明 GPT-4 分析动作的速度比人类专家快，但准确性却比人类专家低，GPT-4 的四种主要错误类型包括冗余/多计、不匹配的分类、不正确的顺序和模糊的识别。研究结果还显示，第 2 步（目的）和第 4 步（结论）是必选步骤，GPT-4 和人类分析的必选率均为 100%。在第 1 步（介绍）、第 3 步（方法）和第 5 步（结论）的某些步骤中出现了差异，在这些步骤中，GPT-4 的必要率往往更高。这项研究揭示了人工智能目前在学术论述中的移动分析能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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International Linguistics Research

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