Two Methods for Internet Buzz Detection Exploiting the Citation Graph

Marie-Jeanne Lesot (1) , François Nel (1) , Thomas Delavallade (1) , Philippe Capet (1) , Bernadette Bouchon-Meunier (1)

1 MALIRE - Machine Learning and Information Retrieval

This paper addresses the task of detecting Internet buzzes, defined as amplification phenomena, i.e. the diffusion on a very large scale of an Internet content, massively taken up within a short period of time. It proposes two approaches based on the citation graph that represents hyperlinks relation between websites. The first method detects temporal abnormalities in the number of citations of an information source, identifying information sources that undergo a surge of their direct citations. The second method exploits higher level cues, based on the definition of the dynamic cumulative visibility of an article. It captures the notion of citation cascade that is central to the specific type of buzzes related to rumour. Both detection approaches are illustrated, respectively on real data extracted from the Web and on realistic simulated data. The experimental study shows the relevance of the proposed methods and highlights their differences.

Domaines: Informatique [cs]

Marie-Jeanne Lesot, François Nel, Thomas Delavallade, Philippe Capet, Bernadette Bouchon-Meunier. Two Methods for Internet Buzz Detection Exploiting the Citation Graph. IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2012, Jun 2012, Brisbane, Australia. pp.1-8, ⟨10.1109/FUZZ-IEEE.2012.6251253⟩. ⟨hal-01271677⟩