Carlos I. Pérez-SechiCastro Cantalejo, JavierGómez González, DanielMartín García, DanielEspínola Vílchez, María RosarioGutiérrez García-Pardo, Inmaculada2026-01-092026-01-092025https://hdl.handle.net/20.500.14352/129723This conference paper explores the visualization of fuzzy measures to model complex interactions between elements in various scenarios. Despite their utility, fuzzy measures present challenges due to the complexity of their interpretation when the number of elements rises. We propose using graphical representations and network analysis techniques to address these challenges. Using the Shapley Index and the Murofushi-Grabisch interaction index, we aim to provide a more intuitive and effective understanding of fuzzy measures. This approach facilitates the visualization and analysis of element interactions, enhancing decision-making processes in complex systems.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/journal articlehttps://link.springer.com/series/7092restricted access51311Decision modelingSoft computingFuzzy MeasuresSocial NetworksGraph TheoryMatemáticas (Matemáticas)Estadística aplicada12 Matemáticas1209 Estadística