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Activity Number: 79
Type: Contributed
Date/Time: Sunday, August 3, 2014 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistical Graphics
Abstract #312348
Title: Gravicom: A Web-Based Tool for Community Detection in Networks
Author(s): Andrea Kaplan*+ and Heike Hofmann and Daniel Nordman
Companies: Iowa State University and Iowa State University and Iowa State University
Keywords: network analysis ; community detection ; visualization ; interactive ; shiny ; D3

The analysis of graphs, in particular the detection of community structures within network data, is of increasing interest across a broad range of disciplines. Current methodology for community detection often involves an algorithmic approach, and commonly partitions a graph into node clusters in an iterative manner before some stopping criterion. Because communities are often fuzzily-defined human concepts, an alternative approach is to leverage the human visual system to identify communities. We present gravicom, a web application built on the R package shiny and the JavaScript library D3, that facilitates detection of community structures through direct user interaction. The application functions as a standalone tool or as an initialization step for use with an objective community detection algorithm. In this paper we discuss the design of gravicom and demonstrate community structure detection using a well-known network dataset.

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