Basave, Amparo Elizabeth Cano

Dadzie, Aba-Sah

Rowe, Matthew

English

Open Research Online (Open)

Open Research OnlineThe Open University’s repository of research publicationsand other research outputsImproving support for web-based visual analysis ofsocial graphsConference or Workshop ItemHow to cite:Dadzie, Aba-Sah; Rowe, Matthew and Basave, Amparo Elizabeth Cano (2009). Improving support for web-based visual analysis of social graphs. In: Proceedings of Putting Visualization on the Web, IEEE VizWeek 2009,11-16 Oct 2009, Atlantic City, USA.For guidance on citations see FAQs.c© 2009 IEEEVersion: Version of RecordCopyright and Moral Rights for the articles on this site are retained by the individual authors and/or other copyrightowners. For more information on Open Research Online’s data policy on reuse of materials please consult the policiespage.oro.open.ac.ukImproving Support for Web-based Visual Analysis of Social GraphsAba-Sah Dadzie∗ Matthew Rowe† Amparo E. Cano‡The OAK Group, Dept. of Computer ScienceThe University of SheffieldABSTRACTWe discuss the options available for web-based visualisation andpresent an argument for the need to support more complex visualanalysis of the interaction that occurs in social media platforms.Index Terms: H.3.5 [Information Storage and Retrieval]: OnlineInformation Services—Web-based services1 INTRODUCTIONAnecdotal evidence and research illustrate the value that visuali-sation brings to the understanding of complex data and scenarios,whether simply to provide an overview of a data set or to supportthe analysis of a situation by enabling greater insight.Visualisation applications usable online are often limited, some-times due to security and bandwidth restrictions, but more impor-tantly because of the lower support of visualisation toolkits andAPIs for web browsers, as well as inherent support in the browsersfor the use of plug-ins. End users tend to work around this challengeby downloading web activity logs and other relevant data in order togenerate visualisations and perform complex analysis offline, afterwhich summaries of their results are captured to a suitable imageformat and posted to their web sites.The power of visualisation can be seen in the adaptation of vari-ous techniques to the solution of real world problems, from simplegraphs and charts in desktop applications used for basic analysis, tohighly sophisticated tools such as AVS1 which provides a suite ofmodules for complex data visualisation and analysis.In this paper we posit that supporting more complex, interactive,visual analysis online should increase insight during the explorationof social media. Social web platforms including microblogging ser-vices such as Twitter2 are becoming increasingly popular. Theseplatforms are overtaking the use of blogs, by allowing web usersto share information socially with their peers and communities ofpractice (CoPs). The exploration of social data is however lim-ited by the sheer amount of data on the web today, therefore newmethodologies must be investigated to support the analytical pro-cess.1.1 Visual Analysis on the WebPrefuse Flare3 (developed to support data visualisation and vi-sual encoding), IBM’s Many Eyes4 (which takes advantage of “hu-man visual intelligence” for collaborative visualisation and infor-mation exploration and discovery), Google Analytics5 (which sup-ports web-based, visual analysis for tracking the content and use of∗e-mail: a.dadzie@dcs.shef.ac.uk†e-mail: m.rowe@dcs.shef.ac.uk‡e-mail: a.cano@dcs.shef.ac.uk1Advanced Visual Systems: http://avs.com2Twitter: http://www.twitter.com3Flare: http://flare.prefuse.org4Many Eyes: http://manyeyes.alphaworks.ibm.com5Google Analytics: http://www.google.com/analyticswebsites), and Exhibit6 (which supports the creation of interactive,visualisation rich websites), are some of the better known, recentlydeveloped toolkits for interactive, online visualisation and analysis.Typical functionality includes switching between graphs, timelines,charts and map-based overviews, among others.1.2 Social DataInformation shared within disparate sources provides an insight intothe dynamics of those platforms. The fragmentation of social datathroughout the web has led to a distribution of data spanning multi-ple communities and contexts. A major challenge of the social dataon the web is making sense of this distributed information.It would be beneficial to analyse how social graphs, generatedby extracting social data to a structured format to aid machine-processing, changes with context or setting. Users on the web shareinformation about multiple topics on different social platforms andmaintain a number of relationships in various social networks.Supporting the exploration of social data for CoPs and the con-textual relationships that occur within this data provides a testbed for investigating analytical methodologies. Moreover, thesemethodologies could be leveraged to other domains of practice,such as expertise determination in enterprise networks, or discover-ing communities of support. This is especially useful for identify-ing and sharing knowledge that has not been formally codified andstored.2 VISUAL ANALYSIS OF ONLINE SOCIAL INTERACTIONOur position in this paper is that current approaches for visualising(online) social data are limited and unable to convey the underly-ing dynamics of the data. To date the visualisation in social graphshas been focused on the representation of the relationships held be-tween the members of a group and the number of steps betweenusers. We would like to see support for visualising trends such aswhich users are contributing to different topics, whether they areinvolved in discussions and if so, where they make positive, criticalor negative contributions.A key benefit of visualising social data would be the depictionof sentimental agreement. The rise in popularity of microbloggingsites allows web users to express their feelings in addition to thetraditional textual responses within topics of discussion. Visualis-ing sentimental trends in such data would support the analysis ofthe overall subjectivity of various topics and the discussions theyengender. This is especially useful for explorative analysis of, forinstance, perceptions of products and services, and political con-sensus of events such as the elections in Iran in 2009 or the coalmine workers’ strikes in England in 1984.The ability to track visually users’ contributions to specifiedthreads should highlight underlying trends within the overview. Forthreads that discuss research or other work-related topics, this couldbe used to weight contributors based on (assumed or defined) ex-pertise, allowing the identification of areas of interest more easily.Exchanges between specified users and the sentiment that accompa-nies the exchange may also enrich the retrieval of knowledge fromthe threads to which they contribute.6Exhibit: http://www.simile-widgets.org/exhibit

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Improving support for web-based visual analysis of social graphs

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