Exploring Accounting Research Topic Evolution: An Unsupervised Machine Learning Approach
June Cao, Zhanzhong Gu, Iftekhar Hasan
Journal of International Accounting Research,
No. 3,
2023
Abstract
This study explores the evolution of accounting research by utilizing an unsupervised machine learning approach. We aim to identify the latent topics of accounting from the 1980s up to 2018, the dynamics and emerging topics of accounting research, and the economic reasons behind those changes. First, based on 23,220 articles from 46 accounting journals, we identify 55 topics using the latent Dirichlet allocation model. To illustrate the connection between topics, we use HistCite to generate a citation map along a timeline. The citation clusters demonstrate the “tribalism” phenomenon in accounting research. We then implement the dynamic topic model to reveal the dynamics of topics to show changes in accounting research. The emerging research trends are identified from the topic analytics. We further explore the economic reasons and in-depth insights into the topic evolution, indicating the economic development embeddedness nature of accounting research.
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22.06.2023 • 16/2023
Revival in service sectors, but industrial activity remains weak for the time being
After the recession during winter, the German economy will expand at a moderate pace in the coming quarters and despite higher interest rates, as private consumption will pick up again with slowly declining inflation and increased wage momentum. In its summer forecast, the Halle Institute for Economic Research (IWH) expects gross domestic product to decline by 0.3% in 2023, while growth of 1.7% is forecast for the coming year.
Oliver Holtemöller
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