Quantifying global polarization: Detection and analysis of opinion groups on the Gaza conflict at international level based on Reddit data

F. Scielzo Ortiz, A. Grané, M. Diaz Gorfinkiel

This research analyzes digital polarization regarding the Gaza conflict using exclusively Reddit data. Avoiding the "platform effect" of mixed-network data, the study leverages Reddit's unified ecosystem and subreddit architecture to capture a diverse ideological spectrum across five discursive frames. By prioritizing top-level comments, it isolates genuine public opinion.

The methodology centers on robust mixed-data clustering. Large Language Models (LLMs) are used to extract critical latent variables from text—such as political stance, sentiment, tone, and argument quality. Crucially, these AI-generated metrics are strictly validated against an expert-coded ground truth to ensure academic reliability.

To prevent popularity bias, clustering relies solely on semantic variables. Platform metadata is reserved for a post-hoc expert interpretation of the predicted clusters. This hybrid framework provides a highly rigorous and reproducible tool for public opinion analysis.

Keywords: Gaza Conflict, Global Polarization, LLM Feature Extraction, Mixed-Data Robust Clustering

GT AMyC I: Advances in Distance-Based Methods
September 4, 2026  9:00 AM
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