PDF-Memetracking and the Dynamics of the News Cycle Jure Leskovec Lars Backstrom Jon Kleinberg

cornelledu larscscornelledu kleinbercscornelledu ABSTRACT Tracking new topics ideas and memes across the Web has been an issue of considerable interest Recent work has developed meth ods for tracking topic shifts over long time scales as well as abru. cmuedu Jon Kleinberg Cornell University kleinbercscornelledu Christos Faloutsos Carnegie Mellon University christoscscmuedu ABSTRACT How do real graphs evolve over time What are normal growth patterns in social technological and information networks Here we suggest a formal perspective on the di57358culty in 57356nding such a uni57356cation in the form of an impossibility theo rem for a set of three simple properties we show that there is no clustering function satisfying all three Relaxations edu Jure Leskovec CS Department Stanford University jurecsstanfordedu Abstract Social media forms a central domain for the production and dissemination of realtime information Even though such 64258ows of information have traditionally been thought o Languages . to Information. Dan Jurafsky. Stanford University. Recommender Systems & Collaborative Filtering. Slides adapted from Jure . Leskovec. Recommender Systems. Customer X. Buys CD of Mozart. Languages . to Information. Dan Jurafsky. Stanford University. Recommender Systems & Collaborative Filtering. Slides adapted from Jure . Leskovec. Recommender Systems. Customer X. Buys CD of Mozart. CS246: Mining Massive Datasets. Jure Leskovec, . Stanford University. http://cs246.stanford.edu. Recap: Finding similar documents. Task:. . Given a large number (. N. in the millions or billions) of documents, find “near duplicates”. CS224W: Social and Information Network Analysis. Jure Leskovec, . Stanford University. http://cs224w.stanford.edu. Overlapping Communities. Non-overlapping vs. overlapping communities. 11/10/2010. Jure Leskovec, Stanford CS224W: Social and Information Network Analysis, http://cs224w.stanford.edu. CS246: Mining Massive Datasets. Jure Leskovec, . Stanford University. http://cs246.stanford.edu. Recap: Finding similar documents. Task:. . Given a large number (. N. in the millions or billions) of documents, find “near duplicates”. Information Flow in Networks. CS224W: Social and Information Network Analysis. Jure Leskovec, . Stanford University. http://cs224w.stanford.edu. Tracking the Information Flow. Imagine you want to track the flow of information. CS224W: Social and Information Network Analysis. Jure . Leskovec. , . Stanford University. http://cs224w.stanford.edu. Today: Signed Networks. Networks with . positive. . and . negative. relationships. CS246: Mining Massive Datasets. Jure Leskovec, . Stanford University. http://cs246.stanford.edu. Learning through Experimentation. Web advertising. We discussed how to . match advertisers to . queries in real-time . CS246: Mining Massive Datasets. Jure Leskovec, . Stanford University. http://cs246.stanford.edu. Learning through Experimentation. Web advertising. We discussed how to . match advertisers to . queries in real-time . 6/14/37 - 7/28/12 Jex Backstrom passed away unexpectedly on Saturday, July 28th in Redding, CA. He is survived by his wonderful wife, Kay Meredith Backstrom, his sons Andrew (Patti) Backstrom of Re Intersection of news media technology and the political processFrom its early stages a tension between global effects from the mass media and local effects carried by social structureHow does informat