Automating Research in Business and Technical Communication: Large Language Models as Qualitative Coders

IF 1.8 2区 文学 Q3 BUSINESS
Ryan M. Omizo
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引用次数: 0

Abstract

The emergence of large language models (LLMs) has disrupted approaches to writing in academic and professional contexts. While much interest has revolved around the ability of LLMs to generate coherent and generically responsible texts with minimal effort and the impact that this will have on writing careers and pedagogy, less attention has been paid to how LLMs can aid writing research. Building from previous research, this study explores the utility of AI text generators to facilitate the qualitative coding research of linguistic data. This study benchmarks five LLM prompting strategies to determine the viability of using LLMs as qualitative coding, not writing, assistants, demonstrating that LLMs can be an effective tool for classifying complex rhetorical expressions and can help business and technical communication researchers quickly produce and test their research designs, enabling them to return insights more quickly and with less initial overhead.
商业和技术交流研究自动化:作为定性编码器的大型语言模型
大型语言模型(LLMs)的出现颠覆了学术和专业背景下的写作方法。虽然人们对大型语言模型以最小的代价生成连贯、通用的文本的能力及其对写作职业和教学法的影响兴趣浓厚,但对大型语言模型如何帮助写作研究却关注较少。在以往研究的基础上,本研究探讨了人工智能文本生成器在促进语言数据定性编码研究方面的效用。本研究以五种 LLM 提示策略为基准,确定将 LLM 作为定性编码(而非写作)助手使用的可行性,证明 LLM 可以成为对复杂修辞表达进行分类的有效工具,并能帮助商业和技术交流研究人员快速生成和测试他们的研究设计,使他们能够以更少的初始开销更快地获得见解。
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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来源期刊
CiteScore
5.10
自引率
18.20%
发文量
16
期刊介绍: JBTC is a refereed journal that provides a forum for discussion of communication practices, problems, and trends in business, professional, scientific, and governmental fields. As such, JBTC offers opportunities for bridging dichotomies that have traditionally existed in professional communication journals between business and technical communication and between industrial and academic audiences. Because JBTC is designed to disseminate knowledge that can lead to improved communication practices in both academe and industry, the journal favors research that will inform professional communicators in both sectors. However, articles addressing one sector or the other will also be considered.
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