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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.
Entropy (Basel, Switzerland)
|December 8, 2020
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.
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.
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