MatLink: Enhanced Matrix Visualization for Analyzing Social Networks
Identifieur interne : 002B01 ( Istex/Corpus ); précédent : 002B00; suivant : 002B02MatLink: Enhanced Matrix Visualization for Analyzing Social Networks
Auteurs : Nathalie Henry ; Jean-Daniel FeketeSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
English descriptors
- KwdEn :
- Additional links, Algorithm, Anova, Answer correctness, Appropriate representation, Average number, Block modeling, Cambridge university press, Cohesive subgroups, Complete graphs, Connectivity tasks, Degree distribution, Dense graphs, Dense networks, Dynamic feedback, Error rate, Experimental evaluation, Fekete, Ghoniem, Good compromise, Graph, Graph visualizations, Higher scores, Human factors, Ieee, Ieee symposium, Information visualization, Infovis toolkit, Large graphs, Layout algorithms, Linear graph, Ltered graphs, Matlink, Matrix, Matrix representation, Matrix representations, Matrix visualization, Mouse pointer, Network analysis, Network analysis tasks, Overall structure, Personal networks, Readability, Readability tasks, Shortest, Shortest cycle, Shortest path, Shortest paths, Shortestpath, Sigchi conference, Small graphs, Social network, Social network analysis, Social networks, Social science researchers, Social sciences, Sparse graphs, Structural analysis, Task taxonomies, User, User feedback, User performance, Vertex area, Visual representations, Visualization.
- Teeft :
- Additional links, Algorithm, Anova, Answer correctness, Appropriate representation, Average number, Block modeling, Cambridge university press, Cohesive subgroups, Complete graphs, Connectivity tasks, Degree distribution, Dense graphs, Dense networks, Dynamic feedback, Error rate, Experimental evaluation, Fekete, Ghoniem, Good compromise, Graph, Graph visualizations, Higher scores, Human factors, Ieee, Ieee symposium, Information visualization, Infovis toolkit, Large graphs, Layout algorithms, Linear graph, Ltered graphs, Matlink, Matrix, Matrix representation, Matrix representations, Matrix visualization, Mouse pointer, Network analysis, Network analysis tasks, Overall structure, Personal networks, Readability, Readability tasks, Shortest, Shortest cycle, Shortest path, Shortest paths, Shortestpath, Sigchi conference, Small graphs, Social network, Social network analysis, Social networks, Social science researchers, Social sciences, Sparse graphs, Structural analysis, Task taxonomies, User, User feedback, User performance, Vertex area, Visual representations, Visualization.
Abstract
Abstract: Visualizing social networks presents challeges for both node-link and adjacency matrix representations. Social networks are locally dense, which makes node-link displays unreadable. Yet, main analysis tasks require following paths, which is difficult on matrices. This article presents MatLink, a hybrid representation with links overlaid on the borders of a matrix and dynamic topological feedback as the pointer moves. We evaluated MatLink by an experiment comparing its readability, in term of errors and time, for social network-related tasks to the other conventional representations on graphs varying in size (small and medium) and density. It showed significant advantages for most tasks, especially path-related ones where standard matrices are weak.
Url:
DOI: 10.1007/978-3-540-74800-7_24
Links to Exploration step
ISTEX:E4AA8468220C4BA1AD4D541BFAA3DF4C0AEF5B89Le document en format XML
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It showed significant advantages for most tasks, especially path-related ones where standard matrices are weak.</abstract><qualityIndicators><refBibsNative>false</refBibsNative><abstractWordCount>108</abstractWordCount><abstractCharCount>768</abstractCharCount><keywordCount>0</keywordCount><score>8.296</score><pdfWordCount>5436</pdfWordCount><pdfCharCount>33979</pdfCharCount><pdfVersion>1.3</pdfVersion><pdfPageCount>15</pdfPageCount><pdfPageSize>430 x 660 pts</pdfPageSize></qualityIndicators><title>MatLink: Enhanced Matrix Visualization for Analyzing Social Networks</title><chapterId><json:string>24</json:string><json:string>Chap24</json:string></chapterId><genre><json:string>conference</json:string></genre><serie><title>Lecture Notes in Computer Science</title><language><json:string>unknown</json:string></language><copyrightDate>2007</copyrightDate><issn><json:string>0302-9743</json:string></issn><eissn><json:string>1611-3349</json:string></eissn><editor><json:item><name>David Hutchison</name></json:item><json:item><name>Takeo Kanade</name></json:item><json:item><name>Josef Kittler</name></json:item><json:item><name>Jon M. 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Social networks are locally dense, which makes node-link displays unreadable. Yet, main analysis tasks require following paths, which is difficult on matrices. This article presents MatLink, a hybrid representation with links overlaid on the borders of a matrix and dynamic topological feedback as the pointer moves. We evaluated MatLink by an experiment comparing its readability, in term of errors and time, for social network-related tasks to the other conventional representations on graphs varying in size (small and medium) and density. It showed significant advantages for most tasks, especially path-related ones where standard matrices are weak.</p></abstract><textClass><keywords scheme="Book-Subject-Collection"><list><label>SUCO11645</label><item><term>Computer Science</term></item></list></keywords></textClass><textClass><keywords scheme="Book-Subject-Group"><list><label>I</label><label>I18067</label><label>I18040</label><label>I21017</label><label>I24032</label><label>I24040</label><label>I14029</label><item><term>Computer Science</term></item><item><term>User Interfaces and Human Computer Interaction</term></item><item><term>Information Systems Applications (incl.Internet)</term></item><item><term>Artificial Intelligence (incl. 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Paris-Sud, F91405, Orsay</OrgName><OrgAddress><Country>France</Country></OrgAddress></Affiliation><Affiliation ID="Aff2"><OrgName>Univ. of Sydney</OrgName><OrgAddress><Country>Australia</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>Visualizing social networks presents challeges for both node-link and adjacency matrix representations. Social networks are locally dense, which makes node-link displays unreadable. Yet, main analysis tasks require following paths, which is difficult on matrices. This article presents MatLink, a hybrid representation with links overlaid on the borders of a matrix and dynamic topological feedback as the pointer moves. We evaluated MatLink by an experiment comparing its readability, in term of errors and time, for social network-related tasks to the other conventional representations on graphs varying in size (small and medium) and density. It showed significant advantages for most tasks, especially path-related ones where standard matrices are weak.</Para></Abstract><KeywordGroup Language="En"><Heading>Keywords</Heading><Keyword>Node-Link Diagram</Keyword><Keyword>Matrix Visualization</Keyword><Keyword>Social Network</Keyword></KeywordGroup></ChapterHeader><NoBody></NoBody></Chapter></SubPart></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>MatLink: Enhanced Matrix Visualization for Analyzing Social Networks</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>MatLink: Enhanced Matrix Visualization for Analyzing Social Networks</title></titleInfo><name type="personal"><namePart type="given">Nathalie</namePart><namePart type="family">Henry</namePart><affiliation>INRIA/LRI, Bat. 490, Univ. Paris-Sud, F91405, Orsay, France</affiliation><affiliation>Univ. of Sydney, Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Jean-Daniel</namePart><namePart type="family">Fekete</namePart><affiliation>INRIA/LRI, Bat. 490, Univ. Paris-Sud, F91405, Orsay, France</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference" displayLabel="proceedings" authority="ISTEX" authorityURI="https://content-type.data.istex.fr" valueURI="https://content-type.data.istex.fr/ark:/67375/XTP-BFHXPBJJ-3"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2007</dateIssued><dateIssued encoding="w3cdtf">2007</dateIssued><copyrightDate encoding="w3cdtf">2007</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><abstract lang="en">Abstract: Visualizing social networks presents challeges for both node-link and adjacency matrix representations. Social networks are locally dense, which makes node-link displays unreadable. Yet, main analysis tasks require following paths, which is difficult on matrices. This article presents MatLink, a hybrid representation with links overlaid on the borders of a matrix and dynamic topological feedback as the pointer moves. We evaluated MatLink by an experiment comparing its readability, in term of errors and time, for social network-related tasks to the other conventional representations on graphs varying in size (small and medium) and density. 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