Exploring Accounting Research Topic Evolution: An Unsupervised Machine Learning Approach
June Cao, Zhanzhong Gu, Iftekhar Hasan
Journal of International Accounting Research,
Nr. 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.
Artikel Lesen
IWH-Insolvenzforschung
IWH-Insolvenzforschung Die IWH-Insolvenzforschungsstelle bündelt die...
Zur Seite
Startseite
IWH-Insolvenztrend für März: Zahl der Firmenpleiten erreicht neuen Rekord Deutlich schneller als die amtliche Statistik...
Zur Seite
IWH European Real Estate Index
IWH European Real Estate Index Die IWH European Real Estate Database ist ein neuer...
Zur Seite
Reports des European Forecasting Network (EFN)
Reports des European Forecasting Network (EFN) Das European Forecasting Network...
Zur Seite
IWH-FDI-Mikrodatenbank
IWH-FDI-Mikrodatenbank Die IWH-FDI-Mikrodatenbank (FDI = Foreign Direct Investment)...
Zur Seite
Schultz wp
The Minimum Wage Effects on Skilled Crafts Sector in Saxony-Anhalt ...
Zur Seite
Wirtschaft im Wandel
Wirtschaft im Wandel Die Zeitschrift „Wirtschaft im Wandel“ will eine breite...
Zur Seite