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Investigating the Spreading and Toxicity of Prion-like Proteins Using the Metazoan Model Organism C. elegans
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Spreading of Competing Information in a Network.

Fabio Bagarello1,2, Francesco Gargano1, Francesco Oliveri3

  • 1Dipartimento di Ingegneria, Università di Palermo, Viale delle Scienze, I-90128 Palermo, Italy.

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Summary

This study models how good and fake news spread through networks. Using ladder fermionic operators, it analyzes conditions under which accurate information overcomes misinformation in network dynamics.

Keywords:
(H,ρ)-induced dynamicsoperatorial modelsspreading of news

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Area of Science:

  • Network Science
  • Information Dynamics
  • Computational Social Science

Background:

  • The spread of information, including misinformation, is a critical aspect of social networks.
  • Understanding the dynamics of 'good news' versus 'fake news' is essential for combating the negative impacts of misinformation.

Purpose of the Study:

  • To develop a model for investigating the spreading dynamics of two competing information types: 'good news' and 'fake news'.
  • To analyze the conditions under which 'good news' can prevail over 'fake news' within a network.

Main Methods:

  • Utilizing a network model to simulate information propagation.
  • Employing ladder fermionic operators to efficiently model dispersion and agent interactions within the network.

Main Results:

  • The study provides a framework for analyzing the competition between accurate information and misinformation.
  • Identifies key factors influencing the success of 'good news' in spreading through a network.

Conclusions:

  • The proposed model offers insights into the complex dynamics of information diffusion in networks.
  • Ladder fermionic operators are effective tools for studying such spreading phenomena and agent interactions.