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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:

Stock Prediction by Integrating Sentiment Scores of Financial News and MLP-Regressor: A Machine Learning Approach
Junaid Maqbool, Preeti Aggarwal, Ravreet Kaur, et al.
Procedia Computer Science (2023) Vol. 218, pp. 1067-1078
Open Access | Times Cited: 44

Showing 1-25 of 44 citing articles:

An interval constraint-based trading strategy with social sentiment for the stock market
Mingchen Li, Kun Yang, Wencan Lin, et al.
Financial Innovation (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 7
SPCM: A Machine Learning Approach for Sentiment-Based Stock Recommendation System
Jiawei Wang, Zhen Chen
IEEE Access (2024) Vol. 12, pp. 14116-14129
Open Access | Times Cited: 4
Using Historical Pattern Matching and Natural Language Processing in a Hybrid Approach for Stock Market
K. Sri Niharika, C.H. Srisai Naga Satya Mani Pavan, T. Aparna, et al.
(2025), pp. 147-165
Closed Access
Knowledge Enhanced Prompt Learning Framework for Financial News Recommendation
Shaobo Sun, Xiaoming Pan, Shuang Qi, et al.
Pattern Recognition (2025), pp. 111461-111461
Closed Access
A Rule-Based Stock Trading Recommendation System Using Sentiment Analysis and Technical Indicators
Yuri Kim, Sua Yoo, Seongbin Park
Electronics (2025) Vol. 14, Iss. 4, pp. 773-773
Open Access
Towards Economic Sustainability: A Comprehensive Review of Artificial Intelligence and Machine Learning Techniques in Improving the Accuracy of Stock Market Movements
Atoosa Rezaei, Iheb Abdellatif, Amjad Umar
International Journal of Financial Studies (2025) Vol. 13, Iss. 1, pp. 28-28
Open Access
Chaos measure dynamics in a multifactor model for financial market predictions
Markus Vogl
Communications in Nonlinear Science and Numerical Simulation (2023) Vol. 130, pp. 107760-107760
Closed Access | Times Cited: 11
Deep Learning and Sentiment Analysis-Based Cryptocurrency Price Prediction
Jia Ming Low, Zi Jian Tan, Tiong Yew Tang, et al.
Lecture notes in computer science (2023), pp. 40-51
Closed Access | Times Cited: 9
Predicting Stock Trends Using Web Semantics and Feature Fusion
Wenrui Zhou, Huxidan Jumahong, Ruihua Cui, et al.
International Journal on Semantic Web and Information Systems (2024) Vol. 20, Iss. 1, pp. 1-25
Open Access | Times Cited: 3
A Multi-Approach Analysis for Monitoring Wave Energy Driven by Coastal Extremes
Reine Matar, Nizar Abcha, Iskander Abroug, et al.
Water (2024) Vol. 16, Iss. 8, pp. 1145-1145
Open Access | Times Cited: 2
Quality prediction for magnetic pulse crimping cable joints based on 3D vision and ensemble learning
Ming Yong Lai, Shaoluo Wang, Hao Jiang, et al.
Computers in Industry (2024) Vol. 162, pp. 104137-104137
Closed Access | Times Cited: 2
Emerging Trends in AI-Based Stock Market Prediction: A Comprehensive and Systematic Review
Rahul Jain, Rakesh Vanzara
(2023), pp. 254-254
Open Access | Times Cited: 6
A Joint Model for Stock Prediction Based on Image and Text Multisource Heterogeneous Data
泓含 昝
Computer Science and Application (2024) Vol. 14, Iss. 01, pp. 88-97
Closed Access | Times Cited: 1
Predicting Diffusion Coefficients in Nafion Membranes during the Soaking Process Using a Machine Learning Approach
Ivan Malashin, D.S. Daibagya, В С Тынченко, et al.
Polymers (2024) Vol. 16, Iss. 9, pp. 1204-1204
Open Access | Times Cited: 1
Comparative Analysis Of Deep Learning Approaches Used For Stock Price Prediction
Ajaykumar K. Kakde, Manisha Dale
(2024), pp. 1-6
Closed Access | Times Cited: 1
Ensemble of hybrid model based technique for early detecting of depression based on SVM and neural networks
Dip Kumar Saha, Tuhin Hossain, Mejdl Safran, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Comparison of Support Vector Machine (SVM) and Linear Regression (LR) for Stock Price Prediction
I Putu Candra Purnama, Ni Luh Wiwik Sri Rahayu Ginantra, I Wayan Agus Surya Darma, et al.
(2023), pp. 1-6
Closed Access | Times Cited: 3
Improvising the Stock Prediction by Integrating with roBERTa and LSTM
N Poornima, D Abilash, M Theodaniel
(2023), pp. 1-8
Closed Access | Times Cited: 2
Multimodal Approach for Painting Price Prediction
Jason Orlando Indrawan, Beatrice Josephine Filia, Chyntia, et al.
2022 4th International Conference on Cybernetics and Intelligent System (ICORIS) (2023), pp. 1-5
Closed Access | Times Cited: 2
Stock Price Prediction Using Sentiment Analysis
Shivani Purwar, Shweta Verma, Smriti Srivastava, et al.
International Journal for Research in Applied Science and Engineering Technology (2024) Vol. 12, Iss. 1, pp. 1301-1305
Open Access
Image-Driven Laser Ablation Optimization
V V Bukhtoyarov, Daniel Ageev, Ivan Malashin, et al.
Research Square (Research Square) (2024)
Open Access
A novel CBAMs-BiLSTM model for Chinese stock market forecasting
Chenhao Cui, Yong Li
JUSTC (2024) Vol. 54, Iss. 2, pp. 0204-0204
Open Access
Predicting Stock Price by Using Attention-Based Hybrid LSTM Model
Jiawei Zhou
Asian Journal of Basic Science & Research (2024) Vol. 06, Iss. 02, pp. 145-158
Open Access
Enhancing Stock Market Prediction Using Gradient Boosting Neural Network: A Hybrid Approach
Taraneh Shahin, María Teresa Ballestar, Ismael Sanz
Computational Economics (2024)
Closed Access
Predicting Sugar Import Quantity Using Multi-Layer Perceptron Regressor Method
Mas Syahdan Filsafan, Riyanarto Sarno, Shintami Chusnul Hidayati, et al.
(2024), pp. 394-399
Closed Access
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