2025/12/15 by Antoine Soetewey, Cédric Heuchenne, Arnaud Claes +1 · 1 voice
Computer Science · Psychology · Social Sciences · #Computational and Text Analysis Methods #Data Analysis with R #Mental Health Research Topics
paper · doi:10.1016/j.softx.2025.102483
openalex created_date 2025/12/15 · openalex publication_date 2025/12/15 · openalex updated_date 2026/07/23
AssociationExplorer is an open-source interactive R Shiny application designed to help non-technical users explore statistical associations within multivariate datasets. Aimed particularly at journalists, educators, and engaged citizens, the tool facilitates the discovery and interpretation of meaningful patterns between variables without requiring programming or statistical expertise. Users can upload structured data (e.g., from surveys or open government datasets), select relevant variables, and dynamically visualize relationships via a correlation network and contextual bivariate plots. To illustrate its capabilities, we present a case study based on the European Social Survey (ESS), showcasing how users can investigate links between attitudes, behaviors, and socio-demographic indicators across countries. The app supports a range of association measures adapted to variable types (Pearson’s r , Eta, and Cramer’s V), ensuring both flexibility and statistical rigor. The visual interface enables users to adjust thresholds for association strength and examine results through interactive graphs and summary tables, making the app particularly well-suited for data storytelling, exploratory research, and public communication. AssociationExplorer demonstrates how open-source statistical tools can enhance transparency, accessibility, and insight in the interpretation of complex social data.