The Impact of External Sources on the Friedkin-Johnsen Model

Fuente: arXiv
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Main Authors: Out, Charlotte, Tu, Sijing, Neumann, Stefan, Zehmakan, Ahad N.
Format: Preprint
Published: 2025
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author Out, Charlotte
Tu, Sijing
Neumann, Stefan
Zehmakan, Ahad N.
author_facet Out, Charlotte
Tu, Sijing
Neumann, Stefan
Zehmakan, Ahad N.
contents To obtain a foundational understanding of timeline algorithms and viral content in shaping public opinions, computer scientists started to study augmented versions of opinion formation models from sociology. In this paper, we generalize the popular Friedkin--Johnsen model to include the effects of external media sources on opinion formation. Our goal is to mathematically analyze the influence of biased media, arising from factors such as manipulated news reporting or the phenomenon of false balance. Within our framework, we examine the scenario of two opposing media sources, which do not adapt their opinions like ordinary nodes, and analyze the conditions and the number of periods required for radicalizing the opinions in the network. When both media sources possess equal influence, we theoretically characterize the final opinion configuration. In the special case where there is only a single media source present, we prove that media sources which do not adapt their opinions are significantly more powerful than those which do. Lastly, we conduct the experiments on real-world and synthetic datasets, showing that our theoretical guarantees closely align with experimental simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2504_08413
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle The Impact of External Sources on the Friedkin-Johnsen Model
Out, Charlotte
Tu, Sijing
Neumann, Stefan
Zehmakan, Ahad N.
Social and Information Networks
To obtain a foundational understanding of timeline algorithms and viral content in shaping public opinions, computer scientists started to study augmented versions of opinion formation models from sociology. In this paper, we generalize the popular Friedkin--Johnsen model to include the effects of external media sources on opinion formation. Our goal is to mathematically analyze the influence of biased media, arising from factors such as manipulated news reporting or the phenomenon of false balance. Within our framework, we examine the scenario of two opposing media sources, which do not adapt their opinions like ordinary nodes, and analyze the conditions and the number of periods required for radicalizing the opinions in the network. When both media sources possess equal influence, we theoretically characterize the final opinion configuration. In the special case where there is only a single media source present, we prove that media sources which do not adapt their opinions are significantly more powerful than those which do. Lastly, we conduct the experiments on real-world and synthetic datasets, showing that our theoretical guarantees closely align with experimental simulations.
title The Impact of External Sources on the Friedkin-Johnsen Model
topic Social and Information Networks
url https://arxiv.org/abs/2504.08413