Schemes of Propagation Models and Source Estimators for Rumor Source Detection in Online Social Networks: A Short Survey of a Decade of Research

TL;DR

This paper surveys a decade of research on rumor source detection in online social networks, focusing on propagation models and estimators, highlighting the importance and challenges of diffusion modeling.

Contribution

It provides a comprehensive overview of three propagation schemes and three source estimators, summarizing key approaches over the past decade.

Findings

Different propagation models capture various rumor spreading patterns.

Various estimators have been developed for rumor source identification.

The survey highlights gaps and future directions in rumor source detection.

Abstract

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.