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09-influence_annot

09-influence_annot - CS224W:...

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CS224W: Social and Information Network Analysis Jure Leskovec Stanford University Jure Leskovec, http://cs224w.stanford.edu
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Due WED Oct 20 MIDNIGHT! Answer the following questions: What is the problem you are solving? Wh d ill ( h ill i )? What data will you use ( how will you get it How will you do the project? Which algorithms/models you plan to develop? Be as specific as you can! Who will you evaluate , measure success? What do you expect to submit/accomplish by the end? Submission instructions: Upload PDF to http://coursework.stanford.edu Get your GroupdID at http://bit.ly/bZmdGA Name your file: <GroupID>_proposal.pdf
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[Leskovec et al., SDM ’07] Posts Blogs Time Information cascade D t Bl ordered hyperlinks Data – Blogs: We crawled 45,000 blogs for 1 year 10 million posts and 350,000 cascades Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 10/13/2009 3
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Cascade shapes (ranked by frequency) The probability of observing a cascade on n nodes follows a ount Zipf distribution: p(n) ~ n -2 Co x = Cascade size (number of nodes) 10/13/2009 4 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu
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Most of cascades are trees r of edges diameter Number Effective d Cascade size (number of nodes) Cascade size Count Count Number of joined cascades C Cascades per node 10/13/2009 5 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu
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What’s a good model? What role does the underlying social network play? C k d li i d Can make a step towards more realistic cascade generation (propagation) model? Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 10/13/2009 6
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1) Randomly pick blog to infect add to cascade 2) Infect each in linked neighbor with probability infect, add to cascade.  B 1 B 2 B 1 B 1 B 1 B 2 B 4 B 3 B 4 B 3 3) Add infected neighbors to cascade. 4) Set node infected in (i) to uninfected. B 1 B 2 B 1 B 1 B 2 B 1 Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu 10/13/2009 7 B 4 B 3 B 4 B 2 B 4 B 3 B 4 B 2
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Generative model Count Count produces realistic cascades: Cascade size Cascade node in degree β =0.025 ount nt Co Cou Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu Most frequent cascades Size of star cascade Size of chain cascade 10/13/2009 8
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