Effectiveness Analysis of Information Dissemination on Social Media Using a Neutrosophic Offsocial Propagation Network Model
Year: 2025
Type: article
Abstract: Social media platforms amplify information dissemination but struggle to model extreme viral trends and harmful content, as traditional models like fuzzy sets and PageRank are limited to a [0,1] range. The Neutrosophic Offsocial Propagation Network Model (NOPNM) addresses this by leveraging Neutrosophic Offsets, Offgraphs, and Offmatrices to represent truth (reach), indeterminacy (uncertainty), and falsehood (harm) in [-2,2]. Neutrosophic theory's extended range outperforms traditional methods, capturing complex dynamics for precise analysis. NOPNM models users or posts as nodes and interactions as edges, using novel operators and metrics grounded in neutrosophic logic. A Twitter case study (SocialImpact2025, June 1-August 31, 2025) validates NOPNM, demonstrating 44% and 53% improvements over fuzzy and probabilistic models, respectively. NOPNM equips content creators with influencer selection tools, platform managers with misinformation detection, and researchers with predictive modeling capabilities.
Authors: Weidong Jiang, Pianpian Wang
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6911984230
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