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dc.contributor.authorFischer, Maximilian T.en_US
dc.contributor.authorSeebacher, Danielen_US
dc.contributor.authorSevastjanova, Ritaen_US
dc.contributor.authorKeim, Daniel A.en_US
dc.contributor.authorEl-Assady, Mennatallahen_US
dc.contributor.editorBorgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana vonen_US
dc.date.accessioned2021-06-12T11:01:17Z
dc.date.available2021-06-12T11:01:17Z
dc.date.issued2021
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14286
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14286
dc.description.abstractCommunication consists of both meta-information as well as content. Currently, the automated analysis of such data often focuses either on the network aspects via social network analysis or on the content, utilizing methods from text-mining. However, the first category of approaches does not leverage the rich content information, while the latter ignores the conversation environment and the temporal evolution, as evident in the meta-information. In contradiction to communication research, which stresses the importance of a holistic approach, both aspects are rarely applied simultaneously, and consequently, their combination has not yet received enough attention in automated analysis systems. In this work, we aim to address this challenge by discussing the difficulties and design decisions of such a path as well as contribute CommAID, a blueprint for a holistic strategy to communication analysis. It features an integrated visual analytics design to analyze communication networks through dynamics modeling, semantic pattern retrieval, and a user-adaptable and problem-specific machine learning-based retrieval system. An interactive multi-level matrix-based visualization facilitates a focused analysis of both network and content using inline visuals supporting cross-checks and reducing context switches. We evaluate our approach in both a case study and through formative evaluation with eight law enforcement experts using a real-world communication corpus. Results show that our solution surpasses existing techniques in terms of integration level and applicability. With this contribution, we aim to pave the path for a more holistic approach to communication analysis.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectHuman centered computing
dc.subjectVisual analytics
dc.subjectApplied computing
dc.subjectLaw
dc.subjectsocial and behavioral sciences
dc.titleCommAID: Visual Analytics for Communication Analysis through Interactive Dynamics Modelingen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersSocial Science, Security, and Accessibility
dc.description.volume40
dc.description.number3
dc.identifier.doi10.1111/cgf.14286
dc.identifier.pages25-36


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  • 40-Issue 3
    EuroVis 2021 - Conference Proceedings

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