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Modeling and analyzing an opinion network dynamics considering the environmental factor.

Fulian Yin1,2, Jinxia Wang2, Xinyi Jiang2

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Mathematical Biosciences and Engineering : MBE
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Summary

This study introduces a new model (NET-OE-SFI) to understand how public opinion evolves on social media, incorporating environmental factors to guide opinion management strategies effectively.

Keywords:
complex networkdynamic modelenvironmental factorsinformation propagationopinion dynamics

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Area of Science:

  • Social Network Analysis
  • Information Propagation Dynamics
  • Computational Social Science

Background:

  • Social media is a key platform for public opinion expression on current events.
  • Understanding opinion evolution is crucial for guiding public discourse and achieving consensus.
  • Existing models often overlook the impact of environmental factors on information spread.

Purpose of the Study:

  • To propose a novel dynamic opinion network model (NET-OE-SFI) that incorporates environmental factors.
  • To analyze the evolution of public opinion influenced by environmental dynamics.
  • To provide insights for effective public opinion management strategies.

Main Methods:

  • Development of the dynamic opinion network susceptible-forwarding-immune (NET-OE-SFI) model.
  • Categorization of forwarding nodes into 'support' and 'opposition' based on user data.
  • Integration of environmental factors, inspired by infectious disease models, into network transmission.

Main Results:

  • The NET-OE-SFI model demonstrates validity through data fitting with real information transmission.
  • Sensitivity analysis reveals the influence of various model parameters on opinion evolution.
  • The model effectively captures the interplay between environmental factors and public opinion dynamics.

Conclusions:

  • The proposed NET-OE-SFI model offers a robust framework for studying public opinion evolution in social networks.
  • Environmental factors significantly impact the spread and transformation of opinions online.
  • The findings contribute to designing more effective strategies for public opinion guidance and management.