工会新闻稿中的模式:如何在劳资关系领域使用结构主题模型

Benedikt Bender, B. Bruinsma
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引用次数: 0

摘要

定量文本分析和大数据集的使用在劳资关系领域只受到有限的关注。考虑到这些方法可以解决的各种机会和可能性,这是不幸的。我们展示了使用一种有前途的定量文本分析技术-结构主题模型(STM) -来测试局内人-局外人理论。这项技术使我们能够在近2000个德国工会新闻稿的文本语料库中找到潜在的主题(从2000年到2014年)。我们提供了一个关于如何使用STM的逐步概述,因为我们认为这种方法对劳资关系领域的未来研究很有用。到目前为止,关于STM的方法学出版物主要集中在该方法的数学上,而对其实现只提供了很少的讨论。相反,我们提供了STM的实际应用,并将这种方法应用于劳资关系领域最突出的理论之一。与最初的内部人-局外人的论点相反,但与目前的研究状况一致,我们表明工会实际上在其新闻稿中使用与内部人和局外人群体相关的主题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Patterns in the Press Releases of Trade Unions: How to Use Structural Topic Models in the Field of Industrial Relations
Quantitative text analysis and the use of large data sets have received only limited attention in the field of Industrial Relations. This is unfortunate, given the variety of opportunities and possibilities these methods can address. We demonstrate the use of one promising technique of quantitative text analysis – the Structural Topic Model (STM) – to test the Insider-Outsider theory. This technique allowed us to find underlying topics in a text corpus of nearly 2,000 German trade union press releases (from 2000 to 2014). We provide a step-by-step overview of how to use STM since we see this method as useful to the future of research in the field of Industrial Relations. Until now the methodological publications regarding STM mostly focus on the mathematics of the method and provide only aminimal discussion of their implementation. Instead, we provide a practical application of STM and apply this method to one of the most prominent theories in the field of Industrial Relations. Contrary to the original Insider-Outsider arguments, but in line with the current state of research, we show that unions do in fact use topics within their press releases which are relevant for both Insider and Outsider groups.
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