As a consequence of the popularization of the social networks , analyzing the information propagation in such networks has bec ome a relevant task in several scenarios. Propagation patterns support th e understanding of phenomena such as opinion formation and the emergence leade rs in social networks. In this paper we present a methodology for propagation a nalysis on Twitter, the most popular micro-blogging service in the Web c urrently. Challenges related to the efficiency and scalability of the metho dology are described and evaluated through its application in a real site, the Obs ervatorio da Web. Resumo. Com a popularizaç̃ ao das chamadas redes sociais, analisar a propagaç̃ao de informaç̃ ao nessas redes se tornou uma tarefa relevante em diversos contextos. Padr ões de propagaç̃ ao podem permitir o entendimento de fen̂omenos como a formaç ̃ o de opinĩ ao e o surgimento de l ı́deres em redes sociais. Neste artigo apresentamos uma metodologia para a an álise de propagaç̃ ao no Twitter, o serviço de micro-blogging mais popular na Web a tualmente. Desafios relacionados̀a eficîencia e escalabilidade de aplicaç ̃ o da metodologia são descritos e avaliados atrav és de uma instanciaç ̃ o em um portal real, o Observat́ orio da Web.
[1]
Devin Gaffney.
#iranElection: quantifying online activism
,
2010
.
[2]
Yutaka Matsuo,et al.
Earthquake shakes Twitter users: real-time event detection by social sensors
,
2010,
WWW '10.
[3]
Ravi Kumar,et al.
Influence and correlation in social networks
,
2008,
KDD.
[4]
Christos Faloutsos,et al.
Patterns of Cascading Behavior in Large Blog Graphs
,
2007,
SDM.
[5]
E. Moro,et al.
Information Diffusion Epidemics in Social Networks
,
2007,
0706.0641.
[6]
Krishna P. Gummadi,et al.
A measurement-driven analysis of information propagation in the flickr social network
,
2009,
WWW '09.
[7]
Krishna P. Gummadi,et al.
Measuring User Influence in Twitter: The Million Follower Fallacy
,
2010,
ICWSM.