PPT-Dynamics of networks Jure Leskovec

Machine Learning Department Carnegie Mellon University Cyberspace The emergence of cyberspace and the World Wide Web is like the discovery of a new continent Jim Gray 1998 Turing Award address. stanfordedu dph kleinbercscornelledu jurecsstanfordedu ABSTRACT An increasingly common feature of online communities and social media sites is a mechanism for rewarding user achievements based on a system of badges Badges are given to users for part stanfordedu sudhof jurafsky cgpottsstanfordedu Abstract We propose a computational framework for identifying linguistic aspects of polite ness Our starting point is a new corpus of requests annotated for politeness which we use to evaluate aspects of 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 stanfordedu cristianmpiswsorg Abstract Social media systems rely on user feedback and rating mechanisms for personalization ranking and content 64257ltering However when users evaluate content con tributed by fellow users eg by liking a post or votin edu Jure Leskovec Stanford University jurecsstanfordedu ABSTRACT Online content exhibits rich temporal dynamics and divers e real time user generated content further intensi64257es this proces s How ever temporal patterns by which online content grow 4 Ibid., p. 54.2 Pacis, p. 170.34 See Chris Hedges, War is a Force that Gives us Meaning, NY: Anchor Books, 2002.35 See my essay, 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. Today: Signed Networks. Networks with . positive. . and . negative. relationships. Languages . to Information. Dan Jurafsky. Stanford University. Recommender Systems & Collaborative Filtering. Slides adapted from Jure . Leskovec. Recommender Systems. Customer X. Buys CD of Mozart. Leskovec. Computer Science Department. Cornell University / Stanford University. Today: Rich data. L. arge on-line systems have detailed records of human activity. On-line communities:. Facebook (64 million users, billion dollar business). The Black Panthers were founded in 1966 by Huey Newton and Bobby Seale. Newton and Seale were greatly inspired by Malcolm X, as well as . Stokely. Carmichael. Stokely. Carmichael, former chairman of SNCC, was a proponent of Black Power. JUSTICE REFORM (DE JURE) Data and Evidence for Justice Reform (DE JURE) The Data and Evidence for Justice Reform (DE JURE) program aims to revolutionize the way we measure, understand and enhance l Introduction to Recommender Systems. Recommender systems: The task. Customer W. 2. Slides adapted from Jure Leskovec. Plays an Ella Fitzgerald song. What should we recommend next?. Thomas . Quella. Wikimedia Commons.