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Publications

Scientific Articles

  • Alaimo S. L., Aria M., D’Aniello L., Spano M. (2026). Scientific Knowledge and Healthcare Quality: A Multidimensional Assessment of Italian Academic Health Science Centres. Applied Stochastic Models in Business and Industry [forthcoming]

  • Aria M., Cuccurullo C., D’Aniello L., Spano M. (2026). SciK-Health: An Open-Data Dashboard for the Multi-Dimensional Evaluation of Academic Health Science Centers. Quality & Quantity [forthcoming]

  • Aria, M., Gnasso, A., Iorio, C., Fokkema, M. (2026) Extending Explainable Ensemble Trees to regression contexts. Applied Stochastic Models in Business and Industry

  • Aria, M., Gnasso, A., Rivieccio, R., Siciliano, R. (2025). Predicting depression in Italy using random forest through the E2Tree methodology. Annals of Operations Research. https://doi.org/10.1007/s10479-025-06758-7

  • Aria, M., Cuccurullo, C., D’Aniello, L., Misuraca, M. & Spano, M. (2025). Sintetizzare la conoscenza:un approccio integrato per l’estrazione di contenuti rilevanti nella letteratura scientifica. Tesi e Temi

  • Aria, M., Gnasso, A., Rivieccio, R., Siciliano, R. (2025). Predicting depression in Italy using Random Forest through the E2Tree methodology. [forthcoming]

  • Durand, JF., Lombardo, R., Camminatiello, I. (2025). Identity spline variations in boosted Partial Least-Squares: a study on poverty. Statistical Methods & Applications. https://doi.org/10.1007/s10260-025-00821-0

  • Lombardo, R., Durand, J.F., Camminatiello, I., & Cuccurullo, C. (2025). Exploring Poverty and SDG Indicators in Italy: An Identity Spline Approach to Partial Least Squares Regression. Econometrics, 13(4), 50. https://doi.org/10.3390/econometrics13040050

  • Aria, M., Cuccurullo, C., D’Aniello, L., Misuraca, M., Spano, M. (2024). Comparative science mapping: a novel conceptual structure analysis with metadata. Scientometrics, 129, 7055–7081. https://doi.org/10.1007/s11192-024-05161-6

  • Beh, E.J., Lombardo, R. (2024) Correspondence Analysis Using the Cressie–Read Family of Divergence Statistics. International Statistical Review, 92(1), 17-42. https://doi.org/10.1111/insr.12541

  • Lombardo, R., Beh E. J., Prattichizzo, F., Lucisano, G., Nicolucci, A., Eliasson, B., Carlsen, H. K., La Grotta, R., Pellegrini, V., Ceriello, A. (2024) Testing and Visualization of Associations in Three-Way Contingency Tables: A Study of the Gender Gap in Patients with Type 1 Diabetes and Cardiovascular Complications. Mathematics, 12 (14), 2186.https://doi.org/10.3390/math12142186

  • Musella, M., Camminatiello, I., Izzo, F. (2024). Caritas’s Work for the Goals of Agenda 2030: A Study on the Services Provided in Campania. Mathematics, 12 (15), 2301.https://doi.org/10.3390/math12152301

  • Takane, Y., Beh, E.J., Lombardo, R. (2024) A theory of contrasts for modified Freeman–Tukey statistics and its applications to Tukey’s post hoc tests for contingency tables. Computational Statistics, 40, 1423–1446.https://doi.org/10.1007/s00180-024-01537-7

  • Wang, T., Beh, E.J., Lombardo, R., Renner, W. I., (2024). Profile Transformations for Reciprocal Averaging and Singular Value Decomposition. Computational Statistics, 40, 1217–1251.https://doi.org/10.1007/s00180-024-01517-x

Proceedings Papers

  • Gnasso, A., Aria, M., Siciliano, R. (2025). From Prediction to Explanation: Interpreting Risk Factors in Health Survey Analytics. In: D’Ambrosio, A., de Rooij, M., De Roover, K., Iorio, C., La Rocca, M. (eds) Supervised and Unsupervised Statistical Data Analysis. CLADAG-VOC 2025. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-032-03042-9_21

  • Gnasso, A., Aria, M. (2025). “Can You Explain That?” E2Tree, SHAP, and LIME for Interpretable Random Forests. In: D’Ambrosio, A., de Rooij, M., De Roover, K., Iorio, C., La Rocca, M. (eds) Supervised and Unsupervised Statistical Data Analysis. CLADAG-VOC 2025. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-032-03042-9_20

  • Aria, M., Cuccurullo, C., D′Aniello, L., Spano, M., Alabiso, C. (2025). From Data Collection to Knowledge in Health: Turning Scientific Production into Practical Decision-Making Tools. In: (a cura di): Giovanna Boccuzzo Enrico Bovo Marica Manisera Luigi Salmaso, IES 2025 - Innovation & Society: Statistics and Data Science for Evaluation and Quality. p. 746-753, Cleup, ISBN: 9788854958494

  • Gnasso, A., Sacco, D., Celardo, L., Smecca, M.A., Alabiso, C., & Spano, M. (2025). Research excellence and patient perception: investigating the impact of AHSCs’ scientific output.. In: (a cura di): Giovanna Boccuzzo Enrico Bovo Marica Manisera Luigi Salmaso, IES 2025 - Innovation & Society: Statistics and Data Science for Evaluation and Quality. Cleup, ISBN: 9788854958494

  • Aria, M., Cuccurullo, C., D’Aniello, L., Misuraca, M., Spano, M. (2025). TALL: A New Shiny App for Text Analysis. In: Pollice, A., Mariani, P. (eds) Methodological and Applied Statistics and Demography III. SIS 2024. Italian Statistical Society Series on Advances in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-031-64431-3_11

  • Camminatiello, I., Iacono, M.P., Lombardo, R. (2025). A Model for the Evaluation of the Italian University System. In: Pollice, A., Mariani, P. (eds) Methodological and Applied Statistics and Demography I. SIS 2024. Italian Statistical Society Series on Advances in Statistics. Springer, Cham.https://doi.org/10.1007/978-3-031-64346-0_26

  • Gnasso, A., Aria, M., Iorio, C., & Fokkema, M. (2025). Explainable Decision Tree Ensembles. In: Pollice, A., Mariani, P. (eds), Methodological and Applied Statistics and Demography IV. SIS 2024. Italian Statistical Society Series on Advances in Statistics. Springer, Cham.https://doi.org/10.1007/978-3-031-64447-4_21

  • Gnasso, A., & Aria, M. (2024). The evolution of Explainable Artificial Intelligence (XAI): a preliminary systematic literature review. In Book of Short Papers of the ASA Conference 2024.

  • Aria, M., Cuccurullo, C., D’Aniello, L., Misuraca, M., Spano, M. (2024). Breaking Barriers with TALL: A Text Analysis Shiny App for ALL. In A. Dister, D. Longrée (eds.), Mots complets, textes déchiffrés (JADT24). Presses Universitaires de Louvain, Vol. 1, pp. 39–48. ISBN: 978-2-39061-471-5

  • Belfiore, M., Spano, M., Cuccurullo, C., Giordano, W. (2024). Beyond Text: Unveiling Corporate Communication Strategies Through Textual Analysis of CEO Letters. In A. Dister, D. Longrée (eds.), Mots complets, textes déchiffrés (JADT24). Presses Universitaires de Louvain, Vol. 1, pp. 69–78. ISBN: 978-2-39061-471-5

  • D’Aniello, L., Robinson-Garcia, N., Aria, M., & Cuccurullo, C. (2024). Decoding Knowledge Claims: The Evaluation of Scientific Publication Contributions through Semantic Analysis. arXiv preprint arXiv:2407.18646. Presented at 28th International Conference on Science, Technology and Innovation Indicators – STI2024, Berlin, 18–20 September 2024.

  • D’Aniello, L., Aria, M., Cuccurullo, C., Misuraca, M., Spano, M. (2024). Extracting knowledge from scientific literature with an integrated Text Summarization approach. In A. Dister, D. Longrée (eds.), Mots complets, textes déchiffrés (JADT24). Presses Universitaires de Louvain, Vol. 1, pp. 239–248. ISBN: 978-2-39061-471-5

  • Gnasso, A., Aria, M., Iorio, C., Fokkema, M. (2025). Explainable Decision Tree Ensembles. In: Pollice, A., Mariani, P. (eds) Methodological and Applied Statistics and Demography IV. SIS 2024. Italian Statistical Society Series on Advances in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-031-64447-4_21

  • Iorio, C., Gnasso, A., & Aria, M. (2024). Inside the black-box models through explainable decision tree ensembles. In Programme and Abstracts – 26th International Conference on Computational Statistics (COMPSTAT 2024), pp. 40–40.

  • Iorio, C., Gnasso, A., & Aria, M. (2024). Inside the black-box models through Explainable Decision Tree Ensembles. COMPSTAT 2024 – 26th International Conference on Computational Statistics, Book of Abstracts.

  • Lombardo, R., Durand, J. F., Camminatiello, I. (2025) Spline identity and functional partial least-squares regression for analysing Italian poverty. In: Pollice A., Mariani P. (eds) Methodological and Applied Statistics and Demography II. SIS 2024. Italian Statistical Society Series on Advances in Statistics. Springer, Cham.https://doi.org/10.1007/978-3-031-64350-7_47

  • Sacco, D., Aria, M., Moccia, S. (2024). Decoding disinformation: A Comprehensive Analysis of Fake News. In A. Dister, D. Longrée (eds.), Mots complets, textes déchiffrés (JADT24). Presses Universitaires de Louvain, Vol. 2, pp. 823–832. ISBN: 978-2-39061-473-9