如何使用自然语言处理进行有效和客观的文献综述:营销研究人员的一步一步指南

Serena Pugliese, Verdiana Giannetti, Sourindra Banerjee
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摘要

文献综述对于充分了解研究的关键主题和最新趋势至关重要,有助于确定重要的研究差距。不幸的是,进行文献综述可能很耗时,而且结果往往是主观的。因此,为了解决这样的限制,我们详细介绍了一种替代的,最近的方法来进行文献综述。在本研究中,我们概述了通过自然语言处理进行文献综述的步骤。具体而言,我们说明了如何(1)使用术语频率-逆文档频率选择相关论文;(2)通过潜在狄利克雷分配进行主题建模分析,以确定关键研究主题。这项研究和相关的现成Python代码为研究人员(包括消费者行为研究人员)提供了如何在其文献综述中使用自然语言处理的详细指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How to conduct efficient and objective literature reviews using natural language processing: A step-by-step guide for marketing researchers
Literature reviews are crucial for attaining a full understanding of the key topics and latest trends in research and instrumental in identifying important research gaps. Unfortunately, conducting literature reviews can be time-consuming, and the outcomes are frequently subjective. Hence, to address such limitations, we detail an alternative, recent approach to conducting literature reviews. In this research, we outline the steps involved in conducting a literature review via natural language processing. Specifically, we illustrate how to (1) select relevant papers using term frequency-inverse document frequency and (2) perform topic modeling analysis through latent Dirichlet allocation to identify key research topics. This study and the associated ready-to-use Python code provide researchers, including those in consumer behavior, with detailed guidance on how to use natural language processing in their literature reviews.
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