Towards large-scale social networks with online diffusion provenance detection

Haishuai Wang, Jia Wu*, Shirui Pan, Peng Zhang, Ling Chen

*Corresponding author for this work

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

In this paper we study a new problem of online discovering diffusion provenances in large networks. Existing work on network diffusion provenance identification focuses on offline learning where data collected from network detectors are static and a snapshot of the network is available before learning. However, an offline learning model does not meet the need for early warning, real-time awareness, or a real-time response to malicious information spreading in networks. To this end, we propose an online regression model for real-time diffusion provenance identification. Specifically, we first use offline collected network cascades to infer the edge transmission weights, and then use an online l1 non-convex regression model as the identification model. The proposed methods are empirically evaluated on both synthetic and real-world networks. Experimental results demonstrate the effectiveness of the proposed model.

Original languageEnglish
Pages (from-to)154-166
Number of pages13
JournalComputer Networks
Volume114
DOIs
Publication statusPublished - 26 Feb 2017
Externally publishedYes

Keywords

  • L₁ Regression
  • Online identification
  • Social network
  • Source locating

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