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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:

Deep Churn Prediction Method for Telecommunication Industry
Lewlisa Saha, Hrudaya Kumar Tripathy, Tarek Gaber, et al.
Sustainability (2023) Vol. 15, Iss. 5, pp. 4543-4543
Open Access | Times Cited: 32

Showing 1-25 of 32 citing articles:

A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners
Awais Manzoor, M. Atif Qureshi, Etain Kidney, et al.
IEEE Access (2024) Vol. 12, pp. 70434-70463
Closed Access | Times Cited: 17
Customer churn prediction in imbalanced datasets with resampling methods: A comparative study
Seyed Jamal Haddadi, Aida Farshidvard, Fillipe dos Santos Silva, et al.
Expert Systems with Applications (2024) Vol. 246, pp. 123086-123086
Closed Access | Times Cited: 14
The role of IoT and XAI convergence in the prediction, explanation, and decision of customer perceived value (CPV) in SMEs: a theoretical framework and research proposition perspective
Kwabena Abrokwah-Larbi
Discover Internet of Things (2025) Vol. 5, Iss. 1
Open Access
Predictive Analytics for Telecom Customer Churn: Enhancing Retention Strategies in the US Market
MD Rashed Mohaimin, B. N. Das, Rabeya Akter, et al.
Journal of Computer Science and Technology Studies (2025) Vol. 7, Iss. 1, pp. 30-45
Closed Access
Churn prediction with GraphSAGE model based on the derived features using RFM and sentiment analysis
M. Anitha, K. K. Sherly
Journal of the Chinese Institute of Engineers (2025), pp. 1-13
Closed Access
Enhancing Employee Churn Prediction with Weibull Time-to-Event Modeling
Hafiza Habiba Shabbir, Muhammad Umar Farooq, Amna Zafar, et al.
Journal of Engineering Research (2025)
Open Access
Predicting customer abandonment in recurrent neural networks using short-term memory
Saul Beltozar-Clemente, Orlando Iparraguirre-Villanueva, Félix Pucuhuayla-Revatta, et al.
Journal of Open Innovation Technology Market and Complexity (2024) Vol. 10, Iss. 1, pp. 100237-100237
Open Access | Times Cited: 3
Realistic Data Delays and Alternative Inactivity Definitions in Telecom Churn: Investigating Concept Drift Using a Sliding-Window Approach
Andrej Bugajev, Rima Kriauzienė, Viktoras Chadyšas
Applied Sciences (2025) Vol. 15, Iss. 3, pp. 1599-1599
Open Access
Archimedes Optimization Algorithm-Based Feature Selection with Hybrid Deep-Learning-Based Churn Prediction in Telecom Industries
Hanan Abdullah Mengash, Nuha Alruwais, Fadoua Kouki, et al.
Biomimetics (2023) Vol. 9, Iss. 1, pp. 1-1
Open Access | Times Cited: 7
Mathematical Modelling and Deep Learning: Innovations in E-Commerce Sentiment Analysis
Et al. Ashish Suresh Awate
Deleted Journal (2024) Vol. 27, Iss. 1, pp. 52-81
Open Access | Times Cited: 2
Customer Experience, Loyalty, and Churn in Bundled Telecommunications Services
Hugo Ribeiro, Belém Barbosa, António Carrizo Moreira, et al.
SAGE Open (2024) Vol. 14, Iss. 2
Open Access | Times Cited: 2
Multi-Layer Perceptron and Radial Basis Function Networks in Predictive Modeling of Churn for Mobile Telecommunications Based on Usage Patterns
Małgorzata Przybyła–Kasperek, Kwabena Frimpong Marfo, Piotr Sulikowski
Applied Sciences (2024) Vol. 14, Iss. 20, pp. 9226-9226
Open Access | Times Cited: 2
Predict customer churn using combination deep learning networks model
Van-Hieu Vu
Neural Computing and Applications (2023) Vol. 36, Iss. 9, pp. 4867-4883
Closed Access | Times Cited: 6
Tri-Strategy Remora Optimization Algorithm based Support Vector Machine for Customer Churn Prediction
Prakash Murugesan, Pragya Trivedi
(2024)
Closed Access | Times Cited: 1
Neural Network Based a Comparative Analysis for Customer Churn Prediction
Anıl Utku, M. Ali Akçayol
Muş Alparslan Üniversitesi Fen Bilimleri Dergisi (2024) Vol. 12, Iss. 1, pp. 39-50
Open Access | Times Cited: 1
An autonomous mixed data oversampling method for AIOT-based churn recognition and personalized recommendations using behavioral segmentation
Ghulam Fatima, Salabat Khan, Farhan Aadil, et al.
PeerJ Computer Science (2024) Vol. 9, pp. e1756-e1756
Open Access | Times Cited: 1
Explaining customer churn prediction in telecom industry using tabular machine learning models
Sumana Sharma Poudel, Suresh Pokharel, Mohan Timilsina
Machine Learning with Applications (2024) Vol. 17, pp. 100567-100567
Open Access | Times Cited: 1
A flexible framework for customer behavior prediction based on ensemble learning
Thi Minh Nguyen, T. Le, Thi-Hau Nguyen
(2023), pp. 126-134
Closed Access | Times Cited: 2
Customer Churn Prediction in Telecommunication and Banking using Machine Learning: A Systematic Literature Review
Habes Ali Altairey, Adel Ismail Al‐Alawi
(2024), pp. 483-490
Closed Access
Cloud-based machine learning algorithms for anomalies detection
R. Amarnath, Gurumoorthi Gurulakshmanan
Indonesian Journal of Electrical Engineering and Computer Science (2024) Vol. 35, Iss. 1, pp. 156-156
Open Access
Data-Driven Decision-Making: Accurate Customer Churn Prediction with Cat-Boost
Bismah Hasan, Zubair Zubair, Shahrukh Ali Shaikh, et al.
Deleted Journal (2024) Vol. 4, Iss. 02
Open Access
Factors, Predictability, and Explainability of Mobile Telephony Customer Departure in Telecommunications Companies: A Systematic Review of the Literature
David Freire, David Mauricio, José L. Castillo, et al.
IEEE Access (2024) Vol. 12, pp. 118968-118980
Open Access
PREDICTION OF CUSTOMER CHURN IN THE BANKING SECTOR: REVIEW
Salma Hassanien, Mohamed Roushdy, Amr Galal, et al.
Journal of Southwest Jiaotong University (2023) Vol. 58, Iss. 4
Open Access | Times Cited: 1
Application of machine learning methods to analyze customer migration risk in terms of corporate financial security
Ramona-Monica Stoica, Radu Vilău, Daniela Voicu, et al.
Systemy Logistyczne Wojsk (2023) Vol. 59, Iss. 2, pp. 169-188
Open Access | Times Cited: 1
A novel artificial intelligent-based approach for real time prediction of telecom customer’s coming interaction
Reyad Hussien, Mohamed Mahgoub, Shahenda Youssef, et al.
Indonesian Journal of Electrical Engineering and Computer Science (2024) Vol. 33, Iss. 1, pp. 540-540
Open Access
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