PPT-Networks with Signed Edges

CS224W Social and Information Network Analysis Jure Leskovec Stanford University httpcs224wstanfordedu Today Signed Networks Networks with positive and negative relationships. with emphasis on information and social networks. T-214-SINE. Summer 2011. Chapter 3. Ýmir Vigfússon. Positive and negative relationships. People are either mutual friends (+) or enemies (-). For now assume a . Paper Review by Rachel Katz. Signed Networks . in . Social Media. Network Structures. Trust network: . Signed, directed. . relations among users indicating . trust (+) or distrust (-) . Social network . in Dynamic Graphs. Viswanath. . Gunturi. (4192285). Bala. . Subrahmanyam. . Kambala. (4451379) . Application Domain. Transportation Networks:. Sample Dataset. Sample dataset showing the dynamic nature . Bipartite Matching. Alexandra Stefan. Flow Network. A . flow network. is a . directed. graph G = (V,E) in which each edge, (. u,v. ) has a . non-negative capacity, c(. u,v. ) ≥ 0. , and for any pair of vertices (. TJTSD66: Advanced Topics in Social Media. (Social . Media . Mining). Dr. WANG, Shuaiqiang @ CS & IS, JYU. Email: . shuaiqiang.wang@jyu.fi. Homepage: . http://users.jyu.fi/~swang/. Why should I use network models?. Christopher Muir. CS 494. Table of Contents. Motivation. *. Definitions. *. History. *. Theory. *. Open Problems. *. Applications. * . Homework. * . References. Motivation. Graphs show the relationships between different objects. Team Formation in Social Networks. Network . Ties. Algorithms for Team Formation. Thanks to . Evimari. Terzi. Boston University. Slideshow Title Goes Here. evimaria@cs.bu.edu. Team-formation problems. Polymatroidal. Networks. Chandra . Chekuri. Univ. of Illinois, Urbana-Champaign. Joint work with . Sreeram. . Kannan. , Adnan Raja, . Pramod. . Viswanath. (UIUC ECE Department). Paper available at http. Erdős-Rényi. Random model, . Watts-. Strogatz. Small-world, . Barabási. -Albert Preferential attachment, . Molloy-Reed . Configuration model . and . Gilbert . Random . G. eometric model. Excellence Through Knowledge. Matching Algorithms and Networks Algorithms and Networks: Matching 2 This lecture Matching: problem statement and applications Bipartite matching (recap) Matching in arbitrary undirected graphs: Edmonds algorithm Why Social Graphs Are Different. Communities. Finding Triangles. Jeffrey D. Ullman. Stanford University/. Infolab. Social Graphs. Graphs can be either directed or undirected.. Example. : The Facebook “friends” graph (undirected).. ). Prof. . Ralucca Gera, . Applied Mathematics Dept.. Naval Postgraduate School. Monterey, California. rgera@nps.edu. Excellence Through Knowledge. Learning Outcomes. I. dentify . network models and explain their structures. 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). We examine how to leverage the information contained within these publication networks, along with information concerning the individual publications themselves and a user’s history, to help predict which entities the user might be most interested in and thus intelligently guide his search..