PPT-Computing Classic Closeness Centrality, at Scale

Edith Cohen Joint with Thomas Pajor Daniel Delling Renato Werneck Very Large Graphs Model relations and interactions edges between entities nodes Call detail email exchanges . kyotouacjp Microsoft Research Asia weicmicrosoftcom Illinois Institute of Technology and Microsoft Research As ia xlicsiitedu Abstract Closeness centrality is an important concept in social net work analysis In a graph representing a social network c C57528 ataly urek Depts Biomedical Informatics Computer Science and Engineering Electrical and Computer Engineering The Ohio State University Email sariyuce1osuedu kamerbmiosuedu esauleunccedu umitbmiosuedu Abstract Centrality metrics have shown to Microdata. with a Robust Privacy Guarantee. Jianneng. Cao,. . National University of Singapore, now at I. 2. R. Panagiotis. . Karras. ,. Rutgers University. Table 2. . Voter registration list. Quasi-identifier (QI):. : Graph-based Centrality as Salience in Text Summarization. Gunes. . Erkan. Department of EECS. University of Michigan. Dragomir. R. . Radev. School of Information & Department of EECS. University of Michigan. Charles L. Cartledge. Michael L. Nelson. Old Dominion University. Department of Computer Science. Norfolk, VA 23529 USA. Why the problem is of interest. Picking apart the title. Preservation. Graph. Suitability. bank. . loans. Christophe J. . Godlewski. UHA & EM Strasbourg. Bulat. . Sanditov. Telecom EM. AFFI . Conference. 2015, Cergy-Pontoise. Take. . away. 2. Financial institutions network and reputation. Edith Cohen. Joint with: . Thomas . Pajor. , . Daniel . Delling. , Renato . Werneck. Microsoft Research . Very Large Graphs. Model many types of relations and interactions (edges) between entities (nodes). TJTSD66: Advanced Topics in Social Media. Dr. WANG, Shuaiqiang @ CS & IS, JYU. Email: . shuaiqiang.wang@jyu.fi. Homepage: . http://users.jyu.fi/~swang/. (Social . Media . Mining). Klout. Why Do We Need Measures?. (Gephi and Python). By: Ralucca Gera, NPS. Excellence Through Knowledge. Python with Networkx. Excellence Through Knowledge. Python code . Use . Metrics.py . from dropbox or . my . website. 3. NetworkX Reference. The “Centralities”. Degree Centrality . 2. The “Centralities”. Quality:. what makes a node important (central). Mathematical. Description. Appropriate Usage. Identification. Lots of one-hop. ). Slides modified from . Lada. . Adamic. and . Dragomir. . Radev. Outline. Degree centrality. Centralization . Betweenness. centrality. Closeness centrality. Eigenvector centrality. Bonacich. power centrality. Quality:. what makes a node important (central). Mathematical. Description. Appropriate Usage. Identification. Lots of one-hop. connections from . The number of vertices that . influences directly. Gephi). Python code . Use . Metrics.py . from . the workshop’s website. 2. NetworkX Reference. PDF reference for NetworkX. Github interactive version. 3. Finding centralities. The part of the. code that finds . The Classic Car Company was created to offer a different kind of support for you, the classic car owner. A company that combines a lifelong passion for classic cars, with a level of customer service more commonly found in leading businesses. A company that will treat your classic car, as if it were our own. Visit: https://www.classiccarcompany.com/