利用机器学习和 ChatGPT 进行商业和管理领域人工智能研究的文献综述

Nazmiye Guler, Samuel N. Kirshner, Richard Vidgen
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引用次数: 0

摘要

本文研究了如何应用人工智能模型和主题建模技术来加强商业、管理和信息系统领域的计算文献综述。该研究强调了有影响力期刊的重要性,并强调了跨学科和跨领域研究的必要性,尤其是在应对人工智能的伦理和监管挑战方面。我们展示了在文献综述过程中结合机器学习和 ChatGPT 的有效性。机器学习用于确定研究主题,而 ChatGPT 则协助研究人员标记主题、生成内容并提高学术写作的效率。通过利用主题建模技术和 ChatGPT,我们发现并标记了文献中的主题,揭示了研究领域的主题结构和内容,使研究人员能够发现有意义的见解,找出研究差距,并突出快速扩展的研究领域。此外,我们还引入了一种识别有影响力论文的方法,有助于弥合计算文献综述与传统文献综述之间的差距,从而为文献综述流程做出贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A literature review of artificial intelligence research in business and management using machine learning and ChatGPT

This paper investigates applying AI models and topic modelling techniques to enhance computational literature reviews in business, management, and information systems. The study highlights the significance of impactful journals and emphasises the need for interdisciplinary and transdisciplinary research, especially in addressing AI's ethical and regulatory challenges. We demonstrate the effectiveness of combining machine learning and ChatGPT in the literature review process. Machine learning is used to identify research topics, and ChatGPT assists researchers in labelling the topics, generating content, and improving the efficiency of academic writing. By leveraging topic modelling techniques and ChatGPT, we uncover and label topics within the literature, shedding light on the thematic structure and content of the research field, allowing researchers to uncover meaningful insights, identify research gaps, and highlight rapidly expanding research areas. Additionally, we contribute to the literature review process by introducing a methodology that identifies impactful papers, helping to bridge the gap between computational literature reviews and traditional literature reviews.

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来源期刊
Data and information management
Data and information management Management Information Systems, Library and Information Sciences
CiteScore
3.70
自引率
0.00%
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审稿时长
55 days
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