PPT-Degree and Eigenvector Centrality

The Centralities Degree Centrality 2 The Centralities Quality what makes a node important central Mathematical Description Appropriate Usage Identification Lots of onehop. Centrality measures. Centrality measures. Centrality is related to the potential importance of a node. Some. nodes have greater “influence” over others compared to the rest,. or are more easily accessible to other, or act as a go-between in. 7. Centrality (. cont. ). Slides modified from . Lada. . Adamic. and . Dragomir. . Radev. Outline. Degree centrality. Centralization . Betweenness. centrality. Closeness centrality. Eigenvector centrality. 3. Network Centrality measures. Introduction to PCA and PLS. K-mean clustering. Protein function prediction using network . concepts. Centrality measures of nodes. Centrality measures. Within graph theory and network analysis, there are various measures of the centrality of a vertex within a graph that determine the . : 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?. Eigenvector Centrality •Node has high score if connected to many –Computed as:•Indicator of popularity, “in the know”•Like degree, is index of exposure, risk•Tends t (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. Some pages are adapted. from Dan Ryan, . Mills College. B. etweenness. Centrality. I. ntuition. : how many pairs of individuals would have to go through you in order to reach one another in the minimum number of hops. 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. Steven Fitzpatrick. Martha Winger-Bearskin. ‘. Intuitive’ Problems . Hamiltonian Problems. Possible Implementations . Traffic Analysis. Spread of Disease. Political Campaigns. Market Analysis. Link Analysis. 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 .