The Frontiers of Society, Science and Technology, 2023, 5(17); doi: 10.25236/FSST.2023.051713.
Chongjian Song
School of Economics and Management, Guangxi Normal University, Guilin, China
To summarize and analyse the relevant topics of massive information content by human power alone will consume a huge amount of time and energy. On the contrary, through the development of information science and other disciplines, the use of big data analytics to extract and analyse the themes of massive text content has appeared in many studies, and LDA is one of the more widely used themes, which can be extracted from a large number of Chinese or English texts to extract the potential themes, and has been applied to a variety of research. It is not uncommon to apply LDA theme model to extract potential topics in a research field. In this paper, we collect relevant literature information in the field of operations management research through crawler technology. Through a series of preprocessing processes, the text content can be processed by the LDA topic model to extract the five topic contents of the text. In order to show the theme content more intuitively, the LDA theme results are further visualized. Finally, the research hotspots in the domestic operation management research field are obtained.
Operations management; Visualization; LDA topic modelling; Text mining
Chongjian Song. Topic Discovery in Operations Management Research Area Based on LDA Topic Modeling. The Frontiers of Society, Science and Technology (2023) Vol. 5, Issue 17: 71-78. https://doi.org/10.25236/FSST.2023.051713.
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