Publications

Network science

Color-avoiding percolation and branching processes

Fekete, P., Molontay, R., Ráth, B., Varga, K. (2024)

Journal of Applied Prorability, 1–25, Cambridge University Press

Progress in the valorization of biomass: a statistical perspective

Barabás, B., Fülöp, O., Nagy, M., & Pályi, G. (2024)

Journal of Mathematical Chemistry, 8, 17, Springer

Color-avoiding connected spanning subgraphs with minimum number of edges

Pintér, J, Varga, K (2024)

Discrete Applied Mathematics 349, 25-43, Elsevier

Towards a better understanding of the characteristics of fractal networks

Zakar-Polyák, E., Nagy, M., & Molontay, R. (2023)

Applied Network Science, 8, 17, Springer

Investigating the origins of fractality based on two novel fractal network models

Zakar-Polyák, E., Nagy, M., & Molontay, R. (2023)

In Complex Networks XIII: Proceedings of the 13th Conference on Complex Networks, CompleNet 2022 (pp. 43-54)

Network classification-based structural analysis of real networks and their model-generated counterparts

Nagy, M. & Molontay, R. (2022)

Network Science, 1-24

Comparative analysis of box-covering algorithms for fractal networks

Kovács, P.T., Nagy, M. & Molontay, R. (2021)

Applied Network Science, 6, 73, Springer

On the structural properties of social networks and their measurement-calibrated synthetic counterparts

Nagy, M., & Molontay, R. (2019)

In Proceedings of The 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 584-588

Transfinite fractal dimension of trees and hierarchical scale-free graphs

Komjáthy, J., Molontay, R., & Simon, K. (2019)

Journal of Complex Networks, 7(5), pp. 764-791

On the Complexity of Color-Avoiding Site and Bond Percolation

Molontay, R., & Varga, K. (2019)

In Proceedings of the 45th International Conference on Current Trends in Theory and Practice of Computer Science, pp. 354-367, Springer

Impact of the Discovery of Fluorous Biphasic Systems on Chemistry: A Statistical and Network Analysis

Barabás, B., Fülöp, O., Molontay, R., & Pályi, G. (2017)

ACS Sustainable Chemistry & Engineering, 5(9), pp. 8108-8118, IEEE

An Interpretable Machine Learning Application for Predicting and Improving University Readiness

Pintér, J., Nagy, M., Köller, D.Á., Szabó, M., Brunáczky, G., Szabó, B. & Molontay, R. (2025)

2025 International Symposium on Educational Technology (ISET), Bangkok, Thailand, 2025, pp. 1-6

Using Machine Learning Methods To Develop Person-Centered Models Predicting STEM Major Choice

Nagy, M., Main, J., Molontay, R., & Griffith, A. (2023)

European Society for Engineering Education (SEFI)

Interpretable Dropout Prediction: Towards XAI-Based Personalized Intervention

Nagy, M., & Molontay, R. (2023)

International Journal of Artificial Intelligence in Education

How to improve the predictive validity of a composite admission score? A case study from Hungary

Molontay, R., & Nagy, M. (2022)

Assessment & Evaluation in Higher Education, 1-19

Assessing the Effects of a Reformed System of Student Evaluation of Teaching

Lukáts, G. D., Berezvai, Z., & Molontay, R. (2022)

Periodica Polytechnica Social and Management Sciences

Teaching Mathematics Online with Increased Empathy in the COVID-19 Pandemic

Fülöp, O., & Nagy, M. (2021)

Opus et Educatio 8(3) (pp. 297-303)

Traits versus Grades — The Incremental Predictive Power of Positive Psychological Factors over Pre-Enrollment Achievement Measures on Academic Performance

Séllei, B., Stumphauser, N., & Molontay, R. (2021)

Applied Sciences

Comprehensive Analysis of the Predictive Validity of University Entrance Score in Hungary

Nagy, M. & Molontay, R. (2021)

Assessment & Evaluation in Higher Education

A kollégiumi lét egyetemi teljesítményre gyakorolt hatásának vizsgálata

Zeleny, K., Molontay, R., & Szabó, M. (2021)

Statisztikai Szemle

BŐVEBBEN

Comparing the effectiveness of two remedial mathematics courses using modern regression discontinuity techniques

Baranyi, M. & Molontay, R. (2020)

Interactive Learning Environments

Interpretable Deep Learning for University Dropout Prediction

Baranyi, M., Nagy, M., & Molontay, R. (2020)

In Proceedings of the 21th Annual SIG Conference on Information Technology Education

Can Professors Buy Better Evaluation with Lenient Grading? - The Effect of Grade Inflation on Student Evaluation of Teaching

Berezvai, Z., Lukáts, G. D., & Molontay, R. (2020)

Assessment & Evaluation in Higher Education

Characterizing Curriculum Prerequisite Networks by a Student Flow Approach

Molontay, R., Horváth, N., Bergmann, J., Szekrényes, D., & Szabó, M. (2020)

IEEE Transactions on Learning Technologies

Kreditrendszerű képzések mintatanterveinek és előtanulmányi hálóinak elemzése a hazai matematika alapszakok példáján

Molontay, R., Horváth, N., Bergmann, J., Szekrényes, D., & Szabó, M. (2020)

Alkalmazott Matematikai Lapok, 37(1), pp. 9-45

Predicting Dropout Using High School and First-semester Academic Achievement Measures

Kiss, B., Nagy, M., Molontay, R., & Csabay, B. (2019)

In Proceedings of the 17th International Conference on Emerging eLearning Technologies and Applications, IEEE

Modeling Students' Academic Performance Using Bayesian Networks

Baranyi, M., Gál, K., Molontay, R., & Csabay, B. (2019)

In Proceedings of the 17th International Conference on Emerging eLearning Technologies and Applications, IEEE

A Web Application for Predicting Academic Performance and Identifying the Contributing Factors

Nagy, M., Molontay, R., & Szabó, M. (2019)

In Proceedings of The 47th SEFI Annual Conference, pp. 1794-1806

A pénzügyi ösztönzők hatása az egyetemi oktatók osztályozási gyakorlatára

Berezvai Z., Lukáts G., & Molontay R. (2019)

Közgazdasági Szemle, 66, pp. 733-750

Effect of Mathematics Remediation on Academic Achievements - a regression discontinuity approach

Baranyi, M., & Molontay, R. (2019)

In Proceedings of the International Symposium on Educational Technology, pp. 29-33, IEEE

Who are the Most Important ,,Suppliers’’ for Universities? - Ranking secondary schools based on their students' university performance

Horváth, N, Molontay, R., & Szabó, M. (2019)

In Proceedings of the 2nd Danube Conference: In search of excellence in higher education, pp. 133-143

Predicting Dropout in Higher Education based on Secondary School Performance

Nagy, M., & Molontay, R. (2018)

In Proceedings of the 22nd International Conference on Intelligent Engineering Systems, pp. 389-394, IEEE

Visualizing Student Flows to Track Retention and Graduation Rates

Horváth, M. D., Molontay, R., & Szabó, M. (2018)

In Proceedings of the 22nd International Conference on Information Visualisation pp. 338-343, IEEE

The Critical Role of Model Selection in Causal Inference: A Comparative Analysis of Classification Models Within the InferBERT Framework for Pharmacovigilance

Kiss, C., Molontay, R., & Pergola, G. (2027)

In P. Andreev, W. Van Woensel, J. Holmes, & A. Sauré (Eds), Artificial Intelligence in Medicine (pp. 174–178)

Continuous glucose monitoring for prediabetes classification in a large real-world cohort: Comparison with HbA1c and fasting plasma glucose

Rákóczi, G., Csányi, D., Molontay, R., Agócs, G., Szentes, B. L., Lee, J., … Sipter, E. (2026)

Diabetes Research and Clinical Practice, 238, 113394

Driving after stroke: A trichotomous logistic regression model to support decision making in uncertain cases

Szabó, G., Pintér, J., Molontay, R., & Fazekas, G. (2025)

Journal of Stroke and Cerebrovascular Diseases, 34(11)

New machine-learning models outperform conventional risk assessment tools in Gastrointestinal bleeding

Boros, E., Pintér, J., Molontay, R., ... & Erőss, B. (2024)

Scientific Reports, 15(1), 1-10

Functional tissue units in the Human Reference Atlas

Bidanta, S., Börner, K., Herr II, B.W., Quardokus, E.M., Nagy, M., Gustilo, K.S., Bajema, R., Maier, E., Molontay, R., & Weber, G.M. (2024)

Nature Communications, 16(1), 1-7

EASY-APP: An artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis

Kui, B., Pintér, J., Molontay, R., Nagy, M., ... & Hungarian Pancreatic Study Group (2022)

Clinical and Translational Medicine, 12(6), e842

Early prediction of acute necrotizing pancreatitis by artificial intelligence: a prospective cohort-analysis of 2387 cases

Kiss, S., Pintér, J., Molontay, R., Nagy, M., ... & Szentesi, A (2022)

Scientific Reports, 12(1), 1-11

Industry-adaptable explainable AI based methodology for forecasting electricity prices

Bíró, B., Kiss, Cs., Molontay, R., & Aszódi, A. (2026)

Energy Conversion and Management: X, 30, 101583

Anticipating Crypto Success: An XAI Framework for Early-Stage Token Viability Using Deployment Features

Bounsavath, A., Kiss, Cs., Savci, T., Hellner, G. & Molontay, R. (2025)

2025 IEEE International Conference on Distributed Ledger Technologies (ICDLT)

LODA Revisited: Enhancements for Robust Online Anomaly Detection with Concept Drift Handling

Szalai, D. M., Baranyi, M., Horváth, G., & Molontay, R. (2025)

2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 933-938

Max–Min semantic chunking of documents for RAG application

Kiss, Cs., Nagy, M., & Szilágyi, P. (2025)

Discover Computing, 28, 117

Tournament schedules and incentives in a double round-robin tournament with four teams

Csató, L., Molontay, R., & Pintér, J. (2023)

International Transactions in Operational Research

Copula-Based Anomaly Scoring of High-Dimensional Data with Application in Telecommunication Networks

Horváth, G., Kovács, E., Molontay, R., & Nováczki, S. (2020)

ACM Transactions on Intelligent Systems and Technology

Markovian Queue with Garbage Collection

Horváth, I., Finta, I., Kovács, F., Mészáros, A., Molontay, R., & Varga, K. (2017)

In Proceedings of the 24th International Conference on Analytical and Stochastic Modelling Techniques and Applications, Lecture Notes in Computer Science, 10378, pp. 109-144, Springer

Cross-Correlation Based Clustering and Dimension Reduction of Multivariate Time Series

Egri, A., Horváth, I., Kovács, F., Molontay, R., & Varga, K. (2017)

In Proceedings of the 21st International Conference on Intelligent Engineering Systems pp. 242-246, IEEE

Fingerprinting and Reconstruction of Functionals of Discrete Time Markov Chains

Egri, A., Horváth, I., Kovács, F., & Molontay, R. (2016)

In the proceedings 23rd International Conference on Analytical and Stochastic Modelling Techniques and Applications, Lecture Notes in Computer Science, 9845, pp. 140-154, Springer

From Beijing to Paris: Media representation and sentiment dynamics of the Olympics and Paralympics across traditional and social platforms (2008–2024)

Amaro, M. & Molontay, R. (2026)

International Journal of Sports Science & Coaching

Cross-platform analysis of diet discourse: scientific research, news media, and social media compared

Kiss, C., Titiz, Ĭ.E., Billy, G., & Molontay, R. (2026)

Social Network Analysis and Mining

Exploring Trends and Future Research Directions in the Adoption of Electric Micromobility Vehicles

Szemere, D., Nguyen, K. H., Nagy, M., & Surman, V. (2026)

Periodica Polytechnica Transportation Engineering

MemeMatch: A Large-Scale Dual-Context Multimodal Dataset and Retrieval System for Internet Memes

Le, D. T. A., Köller, D. Á., Deng, Q. & Molontay, R. (2026)

Proceedings of the International AAAI Conference on Web and Social Media, 20(1), 2828–2838

Investigating banks’ social media content and consumer reactions with machine learning

Gombos, N.J., Vlaszov, A., Bíró-Szigeti, Sz. & Molontay, R. (2025)

Journal of Open Innovation: Technology, Market, and Complexity, 11, 2

Realistic models for diffusion of innovation

Sziklai, B.R., Barnes, K. & Pintér, J. (2025)

Social Network Analysis and Mining, 15, 12, Springer Nature

Topicality boosts popularity: a comparative analysis of NYT articles and Reddit memes

Barnes, K., Juhász, P., Nagy, M., & Molontay. R. (2024)

Social Network Analysis and Mining, 14, 119, Springer Nature

Dank or Not? – Analyzing and Predicting the Popularity of Memes on Reddit

Barnes, K., Riesenmy, T., Trinh, M. D., Lleshi, E., Balogh, N., & Molontay, R. (2021)

Applied Network Science, (6)21

Citation distance matters: towards a new metric for evaluating journal impact

Barnes, K., Bannour, A., Török, L. & Molontay, R. (2026)

Scientometrics 131, 1505–1524

Twenty Years of Network Science: A Bibliographic and Co-Authorship Network Analysis

Molontay, R., & Nagy, M. (2021)

In Big Data and Social Media Analytics (pp. 1-24). Springer, Cham

Two Decades of Network Science: as seen through the co-authorship network of network scientists

Molontay, R., & Nagy, M. (2019)

In Proceedings of The 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp. 578-583

The Co-Authorship Network and Scientific Impact of László Lovász

Barabás B., Fülöp O., & Molontay R. (2019)

Journal of Combinatorial Mathematics and Combinatorial Computing, 108, pp. 187-192