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Interactive Network Visualization of  Research Collaborations using Social Media Data
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Interactive Network Visualization of Research Collaborations using Social Media Data

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Poster presented at GRAND 2013

Poster presented at GRAND 2013
http://grand-nce.ca/events/annual-conference/grand-2013

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Interactive Network Visualization of  Research Collaborations using Social Media Data Interactive Network Visualization of Research Collaborations using Social Media Data Presentation Transcript

  • TEMPLATE DESIGN © 2008www.PosterPresentations.comBackgroundBuilt With…Funding Provided ByTomasz Niewiarowski (tomasz@cs.dal.ca) & Anatoliy Gruzd (gruzd@dal.ca)Dalhousie University, Halifax, Canada[1] Gephi API http://gephi.org/[2] Sigma.js http://sigmajs.org/• GRAND consists of many interconnected networks ofacademics, industry and government partners.• Visualization of these networks is very important forunderstanding of how collaborative and geographicallydistributed teams operate.• Netlytic (http://netlytic.org) is an existing cloud-basedtext and social networks analyzer that can automaticallysummarize large volumes of text and discover socialnetworks from online conversations on social media sitessuch as Twitter, Youtube, blogs, online forums and chats.• The goal is to develop a new and effective networkvisualizer for Netlytic that can offer useful insights intohow to improve collaboration and communicationchannels among research teams as well as assess theireffectiveness and group cohesion.Touch Enable InterfaceAvailable Network Layouts (User-selectable) Mobile Device Friendly:• HTML5 and JavaScriptbased• iPhone, iPad, Android,Windows Surfacesupported• Supports gestures andmulittouch• Works with any modernweb browser• Very efficient - canhandle large-size networksFeatures and InterfaceYifan Hu• Very fast algorithm• Good quality on large graphs• It combines a force-directedmodel with a graphcoarsening techniqueOpenOrd• Very efficient for bignetworks• Long edges are cut to allowclusters to separateForceAtlas• Generally produces a cleanlayout• Good readability for medium-size networksCircular• Good for small-sizenetworks• Draws nodes in a circleordered by a centralitymetric or by an attributeBookClubTwitterNetworkWinterOlympicsTwitterNetworkGraph operations:• Searching, filtering• Adaptive node size based onvarious centrality metrics• Auto clustering for communitydetection• Zooming in/out• Changing network layoutsSupport for collaborativenetwork analysis:• Change network name• Create and share networkimages• Annotate interesting facts?#Grand2012#Grand2011 #Grand2013Twitter Communication Networks Formed During the GRAND Annual ConferencesUser can choose 1 of 4 available network layouts and decide which one is “most informative” for their analysis“most informative”“most informative”