Difference between revisions of "Lin et al KDD 2010"

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== Problem ==
 
== Problem ==
  
In this paper, the authors address a method to [[AddressesProblem::observe and track the popular events or topics]] that evolve over time in the communities. Existing methods separate topics and netword structures apart. In this paper, [[UsesMethod::textual topics and network are combined]] together which makes more sense.
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In this paper, the authors try to [[AddressesProblem::observe and track the popular events or topics]] that evolve over time in the communities.
  
 
== Method ==
 
== Method ==

Revision as of 14:56, 4 February 2011

This is a Paper I read in 10802 social media analysis.

Citation

PET:A Statistical Model for Popular Events Tracking in Social Communities Cindy Xide Lin, Bo Zhao, Qiaozhu Mei, Jiawei Han KDD, 2010

Problem

In this paper, the authors try to observe and track the popular events or topics that evolve over time in the communities.

Method

The authors address the event tracking by first defining a term - Popular Event Tracking (PET) in online communities which includes the popularity of events over time, the burstiness of user interest, information diffusion through the network structure and the evolution of topics.

Dataset

In this paper, the authors select twitter as their source of data.

Results

Here in this paper, the authors compare PET with some other baseline models such as JonK, Cont, BOM and GInt. The authors apply these models to analyze both the Popularity Trend and Network diffusion. The result shows that PET generates the most consistent trends and the smoothest diffusion.