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A rumor spreading model based on information entropy.

Chao Wang1, Zong Xuan Tan2, Ye Ye1

  • 1Department of Mechanical Engineering, Anhui University of Technology, Anhui Ma'anshan, 243002, China.

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|August 31, 2017
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Summary
This summary is machine-generated.

This study introduces a new model for understanding rumor spread based on information entropy. It reveals how trust and distortion tendencies influence the spread of misinformation in online networks.

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Area of Science:

  • Complex Systems
  • Information Science
  • Social Network Analysis

Background:

  • Rumor spreading significantly impacts society, distorting facts and opinions, especially in the current 'post-truth era' characterized by rapid information dissemination.
  • Existing models for rumor spread often rely on contagion or opinion dynamics, potentially overlooking key psychological and social factors.

Purpose of the Study:

  • To develop a comprehensive model for rumor spreading that incorporates information entropy, memory, conformity, and trust dynamics.
  • To analyze the influence of trust (confidence factor β) and distortion propensity (conservation factor K) on rumor dynamics.

Main Methods:

  • A novel model based on information entropy was developed, integrating factors like memory, conformity, and varying trust levels.
  • Simulations were conducted on a Barabási-Albert (BA) scale-free network, initiating with a single piece of information.
  • The impact of confidence (β) and conservation (K) factors on information entropy, opinion fragmentation, and rumor spread range was analyzed.

Main Results:

  • The study quantifies the influence of trust and distortion propensity on the temporal evolution of rumor spread.
  • Key metrics such as average information entropy, opinion fragmentation, and the overall range of rumor dissemination were analyzed in relation to β and K.
  • The model demonstrates how variations in trust and distortion tendencies affect the dynamics of information spread within a network.

Conclusions:

  • The developed information entropy-based model offers a more nuanced understanding of rumor spreading dynamics.
  • Findings provide insights into mitigating the spread of misinformation by understanding the interplay of trust and distortion.
  • This research can inform strategies for decision-making aimed at limiting the propagation of rumors and fake news.