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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Bank distress in the news: Describing events through deep learning
Samuel Rönnqvist, Peter Sarlin
Neurocomputing (2017) Vol. 264, pp. 57-70
Open Access | Times Cited: 66

Showing 1-25 of 66 citing articles:

Deep learning for financial applications : A survey
Ahmet Murat Özbayoğlu, Mehmet Ugur Gudelek, Ömer Berat Sezer
Applied Soft Computing (2020) Vol. 93, pp. 106384-106384
Open Access | Times Cited: 375
Deep learning in finance and banking: A literature review and classification
Huang Jian, Junyi Chai, Stella Cho
Frontiers of Business Research in China (2020) Vol. 14, Iss. 1
Open Access | Times Cited: 177
How are reinforcement learning and deep learning algorithms used for big data based decision making in financial industries–A review and research agenda
Vinay Singh, Shiuann-Shuoh Chen, Minal Singhania, et al.
International Journal of Information Management Data Insights (2022) Vol. 2, Iss. 2, pp. 100094-100094
Open Access | Times Cited: 113
Operational research and artificial intelligence methods in banking
Michael Doumpos, Constantin Zopounidis, Dimitrios Gounopoulos, et al.
European Journal of Operational Research (2022) Vol. 306, Iss. 1, pp. 1-16
Open Access | Times Cited: 96
Predicting distresses using deep learning of text segments in annual reports
Rastin Matin, Casper Worm Hansen, Christian Hansen, et al.
Expert Systems with Applications (2019) Vol. 132, pp. 199-208
Open Access | Times Cited: 78
An ordinal classification framework for bank failure prediction: Methodology and empirical evidence for US banks
Georgios Manthoulis, Michael Doumpos, Constantin Zopounidis, et al.
European Journal of Operational Research (2019) Vol. 282, Iss. 2, pp. 786-801
Closed Access | Times Cited: 58
Predicting innovative firms using web mining and deep learning
Jan Kinne, David Lenz
PLoS ONE (2021) Vol. 16, Iss. 4, pp. e0249071-e0249071
Open Access | Times Cited: 53
Illicit Drivers of Land Use Change: Narcotrafficking and Forest Loss in Central America
Beth Tellman, Steven E. Sesnie, Nicholas R. Magliocca, et al.
Global Environmental Change (2020) Vol. 63, pp. 102092-102092
Open Access | Times Cited: 44
Network connectedness and China's systemic financial risk contagion——An analysis based on big data
Xiaoyun Fan, Yedong Wang, Daoping Wang
Pacific-Basin Finance Journal (2020) Vol. 68, pp. 101322-101322
Closed Access | Times Cited: 43
Forecasting with news sentiment: Evidence with UK newspapers
Dooruj Rambaccussing, Andrzej Kwiatkowski
International Journal of Forecasting (2020) Vol. 36, Iss. 4, pp. 1501-1516
Open Access | Times Cited: 39
Economic Event Detection in Company-Specific News Text
Gilles Jacobs, Els Lefever, Véronique Hoste
(2018)
Open Access | Times Cited: 41
SENTiVENT: enabling supervised information extraction of company-specific events in economic and financial news
Gilles Jacobs, Véronique Hoste
Language Resources and Evaluation (2021) Vol. 56, Iss. 1, pp. 225-257
Open Access | Times Cited: 31
Ensemble deep learning framework for stock market data prediction (EDLF-DP)
Vaishali Ingle, Sachin N. Deshmukh
Global Transitions Proceedings (2021) Vol. 2, Iss. 1, pp. 47-66
Open Access | Times Cited: 30
Assessing the performance of banks through an improved sigma-mu multicriteria analysis approach
Silvia Angilella, Michael Doumpos, Maria Rosaria Pappalardo, et al.
Omega (2024) Vol. 127, pp. 103099-103099
Open Access | Times Cited: 4
Analysis of early warning of corporate financial risk via deep learning artificial neural network
Feng Qi, Han Chen, Ruohan Jiang
Microprocessors and Microsystems (2021) Vol. 87, pp. 104387-104387
Closed Access | Times Cited: 23
Operational Research and Artificial Intelligence Methods in Banking
Michael Doumpos, C. Zopounidis, Dimitrios Gounopoulos, et al.
SSRN Electronic Journal (2022)
Open Access | Times Cited: 16
Financial Event Extraction Using Wikipedia-Based Weak Supervision
Liat Ein‐Dor, Ariel Gera, Orith Toledo‐Ronen, et al.
(2019), pp. 10-15
Open Access | Times Cited: 28
Deep Learning and Implementations in Banking
Hossein Hassani, Xu Huang, Emmanuel Sirimal Silva, et al.
Annals of Data Science (2020) Vol. 7, Iss. 3, pp. 433-446
Open Access | Times Cited: 27
Assessing News Contagion in Finance
Paola Cerchiello, Giancarlo Nicola
Econometrics (2018) Vol. 6, Iss. 1, pp. 5-5
Open Access | Times Cited: 27
Predicting Financial Prices of Stock Market using Recurrent Convolutional Neural Networks
Rana Muhammad Zulqarnain, Rozaida Ghazali, Muhammad Ghulam Ghouse, et al.
International Journal of Intelligent Systems and Applications (2020) Vol. 12, Iss. 6, pp. 21-32
Open Access | Times Cited: 22
Learning risk culture of banks using news analytics
Arvind Agarwal, Aparna Gupta, Arun Kumar, et al.
European Journal of Operational Research (2019) Vol. 277, Iss. 2, pp. 770-783
Closed Access | Times Cited: 21
Combining contextual neural networks for time series classification
Amadu Fullah Kamara, Enhong Chen, Qi Liu, et al.
Neurocomputing (2019) Vol. 384, pp. 57-66
Closed Access | Times Cited: 20
Artificial Intelligence and Machine Learning in Financial Services to Improve the Business System
Komalpreet Kaur, Yogesh Kumar, Sukhpreet Kaur
Disruptive technologies and digital transformations for society 5.0 (2023), pp. 3-30
Closed Access | Times Cited: 6
An interpretable neural fuzzy inference system for predictions of underpricing in initial public offerings
Di Wang, Xiaolin Qian, Chai Quek, et al.
Neurocomputing (2018) Vol. 319, pp. 102-117
Open Access | Times Cited: 17
Predicting Innovative Firms Using Web Mining and Deep Learning
Jan Kinne, David Lenz
SSRN Electronic Journal (2019)
Open Access | Times Cited: 14
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