Topic modeling

Vern L. Glaser, Timothy R. Hannigan and P. Devereaux Jennings

Chapter 3.18 in Elgar Encyclopedia of Strategy as Practice, 2025, pp 353-357 from Edward Elgar Publishing

Abstract: Topic modeling is a natural language processing-based (NLP) technique used for analyzing content in large collections of texts. It does not rely on artificial intelligence, but rather is an approach that involves varying degrees of human supervision and interpretation to discover topics as coding categories. This is usually conducted with large collections of texts (or documents) referred to as a corpus. Topic modeling is likely of interest to an SAP scholar because it is most useful with a large textual corpus of at least 35,000 words and a few hundred documents; it relies on linguistic principles to create topics across documents; it employs several relatively transparent steps to render a quality model; and it can be adjusted to include temporal dynamics by period or around key constructs.

Keywords: Topic Modeling; NLP; LDA; STM; Textual corpora; Classification (search for similar items in EconPapers)
Date: 2025
ISBN: 9781035315956
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