Spreading predictability in complex networks

作者：Na Zhao, Jian Wang, Yong Yu, Junyan Zhao, Duanbing Chen · 发表于：bioRxiv (Cold Spring Harbor Laboratory) · 年份：2020 · DOI：10.1101/2020.01.28.922757 · 被引用次数：2 · 研究领域：Complex Network Analysis Techniques、Opinion Dynamics and Social Influence、Evolutionary Game Theory and Cooperation

Abstract Spreading dynamics analysis is an important and interesting topic since it has many applications such as rumor or disease controlling, viral marketing and information recommending. Many state-of-the-art researches focus on predicting infection scale or threshold. Few researchers pay attention to the predicting of infection nodes from a snapshot. With developing of precision marketing, recommending and, controlling, how to predict infection nodes precisely from snapshot becomes a key issue in spreading dynamics analysis. In this paper, a probability based prediction model is presented so as to estimate the infection nodes from a snapshot of spreading. Experimental results on synthetic and real networks demonstrate that the model proposed could predict the infection nodes precisely in the sense of probability.