{"title":"Keynote address: Why everyone seems to be using spring embedders for network visualization, and should not","authors":"U. Brandes","doi":"10.1109/PACIFICVIS.2011.5742366","DOIUrl":null,"url":null,"abstract":"The main algorithmic challenge in network visualization is the placement of nodes. While plenty of layout algorithms have been proposed, the vast majority of information visualization tools appears to utilize (sometimes a variant of) one of two algorithms: the approach of Fruchterman and Reingold or that of Kamada and Kawai. Both are often referred to as force-directed methods, or spring embedders, and praised for their general applicability, high adaptability, and simplicity. I will argue that commonly used implementations and even the approaches themselves are outdated and, in fact, have always been. They should be replaced by variants of multidimensional scaling that display superior results and scalability, and are just as flexible and easy to implement. Some of these statements may actually be backed by evidence.","PeriodicalId":127522,"journal":{"name":"2011 IEEE Pacific Visualization Symposium","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE Pacific Visualization Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACIFICVIS.2011.5742366","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The main algorithmic challenge in network visualization is the placement of nodes. While plenty of layout algorithms have been proposed, the vast majority of information visualization tools appears to utilize (sometimes a variant of) one of two algorithms: the approach of Fruchterman and Reingold or that of Kamada and Kawai. Both are often referred to as force-directed methods, or spring embedders, and praised for their general applicability, high adaptability, and simplicity. I will argue that commonly used implementations and even the approaches themselves are outdated and, in fact, have always been. They should be replaced by variants of multidimensional scaling that display superior results and scalability, and are just as flexible and easy to implement. Some of these statements may actually be backed by evidence.