The physics of news, rumors, and opinions
15 affiliations
- 1DSMN and ECLT, Ca’Foscari University of Venice, Italy
- 2Istituto dei Sistemi Complessi CNR-ISC Rome, Italy
- 3London Institute for Mathematical Science, Royal Institution, London, UK
- 4Departament de Fisica de la Materia Condensada, Universitat de Barcelona, 08028 Barcelona, Spain
- 5Universitat de Barcelona Institute of Complex Systems (UBICS), Universitat de Barcelona, 08028 Barcelona, Spain
- 6Zurcher Hochschule fuer Angewandte Wissenschaften (ZHAW), Zurich, Switzerland
- 7CNR-IAC Istituto per le Applicazioni del Calcolo, Roma, Italy
- 8Florida Atlantic University, USA
- 9University of Warsaw, Poland
- 10Centro Studi e Ricerche e Museo della Fisica “Enrico Fermi” Rome, Italy
- 11IMT School For Advanced Studies Lucca, Italy
- 12Istituto dei Sistemi Complessi CNR-IAC Florence, Italy
- 13Department of Computer Science, Aalto University, Finland
- 14Department of Physics, University of Padova, Padua, Italy
- 15INFN Sez. Padova, Padua, Italy
Abstract
The boundaries between physical and social networks have narrowed with the advent of the Internet and its pervasive platforms. This has given rise to a complex adaptive information ecosystem where individuals and machines compete for attention, leading to emergent collective phenomena. The flow of information in this ecosystem is often non-trivial and involves complex user strategies—from the forging or strategic amplification of manipulative content to large-scale coordinated behavior—that trigger misinformation cascades, echo-chamber reinforcement, and opinion polarization. We argue that statistical physics provides a suitable and necessary framework for analyzing the unfolding of these complex dynamics on socio-technological systems. This review systematically covers the foundational and applied aspects of this framework. The review is structured to first establish the theoretical foundation for analyzing these complex systems, examining both structural models of complex networks and physical models of social dynamics (e.g., epidemic and spin models). We then ground these concepts by describing the modern media ecosystem where these dynamics currently unfold, including a comparative analysis of platforms and the challenge of information disorders. The central sections proceed to apply this framework to two central phenomena: first, by analyzing the collective dynamics of information spreading, with a dedicated focus on the models, the main empirical insights, and the unique traits characterizing misinformation; and second, by reviewing current models of opinion dynamics, spanning discrete, continuous, and coevolutionary approaches. In summary, we review both empirical findings based on massive data analytics and theoretical advances, highlighting the valuable insights obtained from physics-based efforts to investigate these phenomena of high societal impact.
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BibTeX
@article{caldarelli2026physics,
title = {{The physics of news, rumors, and opinions}},
author = {Guido Caldarelli and Oriol Artime and Giulia Fischetti and Stefano Guarino and Andrzej K. Nowak and Fabio Saracco and Petter Holme and Manlio De Domenico},
journal = {Physics Reports},
year = {2026},
month = may,
doi = {10.1016/j.physrep.2026.05.002},
url = {https://doi.org/10.1016/j.physrep.2026.05.002},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - The physics of news, rumors, and opinions
AU - Guido Caldarelli
AU - Oriol Artime
AU - Giulia Fischetti
AU - Stefano Guarino
AU - Andrzej K. Nowak
AU - Fabio Saracco
AU - Petter Holme
AU - Manlio De Domenico
PY - 2026
DA - 2026/05/29
JO - Physics Reports
DO - 10.1016/j.physrep.2026.05.002
UR - https://doi.org/10.1016/j.physrep.2026.05.002
AB - The boundaries between physical and social networks have narrowed with the advent of the Internet and its pervasive platforms. This has given rise to a complex adaptive information ecosystem where individuals and machines compete for attention, leading to emergent collective phenomena. The flow of information in this ecosystem is often non-trivial and involves complex user strategies—from the forging or strategic amplification of manipulative content to large-scale coordinated behavior—that trigger misinformation cascades, echo-chamber reinforcement, and opinion polarization. We argue that statistical physics provides a suitable and necessary framework for analyzing the unfolding of these complex dynamics on socio-technological systems. This review systematically covers the foundational and applied aspects of this framework. The review is structured to first establish the theoretical foundation for analyzing these complex systems, examining both structural models of complex networks and physical models of social dynamics (e.g., epidemic and spin models). We then ground these concepts by describing the modern media ecosystem where these dynamics currently unfold, including a comparative analysis of platforms and the challenge of information disorders. The central sections proceed to apply this framework to two central phenomena: first, by analyzing the collective dynamics of information spreading, with a dedicated focus on the models, the main empirical insights, and the unique traits characterizing misinformation; and second, by reviewing current models of opinion dynamics, spanning discrete, continuous, and coevolutionary approaches. In summary, we review both empirical findings based on massive data analytics and theoretical advances, highlighting the valuable insights obtained from physics-based efforts to investigate these phenomena of high societal impact.
SN - 0370-1573
SN - 1873-6270
ER -