Title
Two Methods For Internet Buzz Detection Exploiting The Citation Graph
Abstract
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.
Year
DOI
Venue
2012
10.1109/FUZZ-IEEE.2012.6251253
2012 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE)
Keywords
Field
DocType
data mining,citation analysis,web pages,graph theory,data models,internet
Graph theory,Data mining,Data modeling,Web page,Information retrieval,Computer science,Citation,Citation analysis,Citation graph,Hyperlink,The Internet
Conference
ISSN
Citations 
PageRank 
1098-7584
0
0.34
References 
Authors
10
5
Name
Order
Citations
PageRank
Marie-Jeanne Lesot122032.41
François Nel201.01
Thomas Delavallade3152.70
Philippe Capet491.99
Bernadette Bouchon-meunier51033173.38