Quantifying opinion homophily in online social networks from a bounded confidence perspective

Zenodo (CERN European Organization for Nuclear Research) 2026 Dataset Open access

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Authors: Yangyang Luan, Camilla Ancona, Carmela Bernardo, Valentina Pansanella, Francesco Lo Iudice, Giulio Rossetti, Francesco Vasca, Xiaoqun Wu, Claudio Altafini
DOI: 10.5281/zenodo.20587478
Cited by: 1

Abstract

This record contains the processed Twitter-Covid dataset and MATLAB code associated with the article "Quantifying opinion homophily in online social networks from a bounded confidence perspective", published in Communications Physics, 9, 240 (2026), https://doi.org/10.1038/s42005-026-02760-y. The shared dataset uses anonymized consecutive internal node indices and contains no original platform user identifiers.

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
8 June 2026
Language
EN
Document type
Dataset