RT Journal Article
T1 Quantifying the potentiality for polarization in opinion networks
A1 Carballosa Calleja, Alejandro
A1 Crego, Álvaro
A1 Pérez Muñuzuri, Alberto
K1 Opinion formation
K1 Complex networks
K1 Opinion polarization
K1 Turing
AB Polarization in debates and social networks is a phenomenon clearly present in modern societies that strongly modifies the way we relate as communities. Regardless of the importance of this phenomenon, there is not a clear explanation yet for its emergence or a suitable parameter to quantify it. Here, we present a methodology based on the Turing instability, a frequent mechanism in Nature which explains differentiation processes, that maps the conditions needed for a given network to undergo polarization of opinions. From this mapping, we measure the likelihood of the system's nodes to differentiate each other or, in other terms, the degree of polarization of the network
PB Elsevier
SN 0960-0779
YR 2023
FD 2023-06-21
LK http://hdl.handle.net/10347/31186
UL http://hdl.handle.net/10347/31186
LA eng
NO Chaos, Solitons & Fractals 173 (2023) 113697
NO We gratefully acknowledge financial support by the Spanish Ministerio de Economía y Competitividad and European Regional Development Fund under contract RTI2018-097063-B-I00 AEI/FEDER, UE, and by Xunta de Galicia under Research Grant No. 2021-PG036. All these programs are co-funded by FEDER (UE). A. Carballosa acknowledges financial support from Xunta de Galicia. The simulations were run in the Supercomputer Center of Galicia (CESGA) and we acknowledge their support
DS Minerva
RD 6 jun 2026