Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Complex Network Analysis Techniques
Abstract
This paper investigates the temporal dynamics of information flow within social networks, focusing on the propagation of novelty. The core claim is to develop a computational framework to model the spread of information and novelty, providing insights into collective behavior and influence. We propose a system that simulates the propagation of information through a network based on exposure, reciprocity, and social influence, utilizing a dynamic Bayesian network to capture the complex interplay of these factors. The model aims to address current limitations in existing models, particularly in understanding the nuanced dynamics of novelty diffusion. This research utilizes a computational approach to explore how these factors interact over time, ultimately offering a framework for analyzing and predicting the spread of information within social networks.
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