Major Information Visualization Authors, Papers and Topics in the ACM Library

Weimao Ke · Katy Börner

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scientometrics and bibliometrics research Complex Network Analysis Techniques Data Visualization and Analytics

Abstract

The presented work aims to identify major research topics, coauthorships, and trends in the IV Contest 2004 dataset. Co-author, paper-citation, and burst analysis were used to analyze the dataset. The results are visually presented as graphs, static Pajek [1] visualizations and interactive network layouts using Pajek’s SVG output feature. A complementary web page with all the raw data, details of the analyses, and high resolution images of all figures is available online at

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2004The simultaneous evolution of author and paper networks

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2011How to Become a Group Leader? or Modeling Author Types Based on Graph Mining 2006Analysis and Visualization of Co-authorship Networks for Understanding Academic Collaboration and Knowledge Domain of Individual Researchers 2013Development of multidimensional academic information networks with a novel data cube based modeling method 2012A fitness model for scholarly impact analysis 2013Visual exploration of academic career paths 2008Co-author Network Analysis in DBLP: Classifying Personal Names

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