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Recent years have seen various rumor diffusion models being assumed in detection of rumor source research of the online social network. Diffusion model is arguably considered as a very important and challengeable factor for source detection in networks but it is less studied. This paper provides an overview of three representative schemes of Independent Cascade-based, Epidemic-based, and Learning-based to model the patterns of rumor propagation as well as three major schemes of estimators for rumor sources since its inception a decade ago.
Social media, such as Facebook and Twitter, has become one of the most important channels for information dissemination. However, these social media platforms are often misused to spread rumors, which has brought about severe social problems, and con
Classification problems have made significant progress due to the maturity of artificial intelligence (AI). However, differentiating items from categories without noticeable boundaries is still a huge challenge for machines -- which is also crucial f
A common goal in network modeling is to uncover the latent community structure present among nodes. For many real-world networks, observed connections consist of events arriving as streams, which are then aggregated to form edges, ignoring the tempor
Protein interactions constitute the fundamental building block of almost every life activity. Identifying protein communities from Protein-Protein Interaction (PPI) networks is essential to understand the principles of cellular organization and explo
Over the past decade, online social networks (OSNs) such as Twitter and Facebook have thrived and experienced rapid growth to over 1 billion users. A major evolution would be to leverage the characteristics of OSNs to evaluate the effectiveness of th