The EFA Annual Meeting 2020 in Helsinki, Finland: Conference Digitalization and Textual Analyses of EFA Papers 2009 and 2010
JOURNAL ARTICLE
Cite JOURNAL ARTICLE
Style
Format
The EFA Annual Meeting 2020 in Helsinki, Finland: Conference Digitalization and Textual Analyses of EFA Papers 2009 and 2010
Credit and Capital Markets – Kredit und Kapital, Vol. 54 (2021), Iss. 1 : pp. 117–131
Additional Information
Article Details
Author Details
Univ.-Prof. Dr. Wolfgang Breuer, Rheinisch-Westfälische Technische Hochschule Aachen, Department of Finance, School of Business and Economics, RWTH Aachen University, Templergraben 64, D-52056 Aachen.
References
-
Blei, D. M./Ng, A. Y./Jordan, M. I. (2003): Latent dirichlet allocation. Journal of Machine Learning Research Vol. 3(1): 993–1022.
Google Scholar -
Breuer, W./Steininger, B. I. (2020): Recent trends in real estate research: a comparison of recent working papers and publications using machine learning algorithms. Journal of Business Economics Vol. 90 (1): 963–974.
Google Scholar -
Dyer, T./Lang, M./Stice-Lawrence, L. (2017): The evolution of 10-K textual disclosure: evidence from latent dirichlet allocation, Journal of Accounting and Economics Vol. 64 (2): 221–245.
Google Scholar -
Silge, J./Robinson, D. (2016): tidytext: text mining and analysis using tidy data principles in R, Journal of Open Source Software Vol. 3(1): 37.
Google Scholar -
Breuer, W./Steininger, B. I. (2020): Recent trends in real estate research: a comparison of recent working papers and publications using machine learning algorithms. Journal of Business Economics Vol. 90 (1): 963–974.
Google Scholar -
Blei, D. M./Ng, A. Y./Jordan, M. I. (2003): Latent dirichlet allocation. Journal of Machine Learning Research Vol. 3(1): 993–1022.
Google Scholar -
Dyer, T./Lang, M./Stice-Lawrence, L. (2017): The evolution of 10-K textual disclosure: evidence from latent dirichlet allocation, Journal of Accounting and Economics Vol. 64 (2): 221–245.
Google Scholar -
Silge, J./Robinson, D. (2016): tidytext: text mining and analysis using tidy data principles in R, Journal of Open Source Software Vol. 3(1): 37.
Google Scholar