In recent years, the rapid proliferation of fake news on social media platforms has posed significant challenges, influencing public opinion, political decisions, and societal dynamics. To address this issue, we propose a novel logic-based framework leveraging News-Diffusion Temporal Logic (NDTL) to analyze and characterize distinctive temporal diffusion patterns of fake and true news. Our approach systematically identifies temporal propagation behaviors through automatically generated logical formulas, enabling transparent and interpretable news classification. Through extensive experimental evaluations on news diffusion datasets, we demonstrate the framework’s capability to distinguish between fake and true news diffusion dynamics effectively.
Logic-based analysis of fake news diffusion on social media
Fionda V.
2025-01-01
Abstract
In recent years, the rapid proliferation of fake news on social media platforms has posed significant challenges, influencing public opinion, political decisions, and societal dynamics. To address this issue, we propose a novel logic-based framework leveraging News-Diffusion Temporal Logic (NDTL) to analyze and characterize distinctive temporal diffusion patterns of fake and true news. Our approach systematically identifies temporal propagation behaviors through automatically generated logical formulas, enabling transparent and interpretable news classification. Through extensive experimental evaluations on news diffusion datasets, we demonstrate the framework’s capability to distinguish between fake and true news diffusion dynamics effectively.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
