@inproceedings{Wanner2014State-30007,
  year={2014},
  doi={10.2312/eurovisstar.20141176},
  title={State-of-the-Art Report of Visual Analysis for Event Detection in Text Data Streams},
  publisher={Eurographics Association},
  booktitle={EuroVis 2014 : the Eurographics Conference on Visualization ; 9-13 June 2014, Swansea, Wales, UK ; EuroVis - STARs},
  pages={125--139},
  editor={Margit Pohl ...},
  author={Wanner, Franz and Stoffel, Andreas and Jäckle, Dominik and Kwon, Bum Chul and Weiler, Andreas and Keim, Daniel A.}
}

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    <dc:creator>Stoffel, Andreas</dc:creator>
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    <dc:contributor>Weiler, Andreas</dc:contributor>
    <dc:contributor>Stoffel, Andreas</dc:contributor>
    <dc:language>eng</dc:language>
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    <dc:contributor>Jäckle, Dominik</dc:contributor>
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    <dcterms:abstract xml:lang="eng">Event detection from text data streams has been a popular research area in the past decade. Recently, the evolution of microblogging and social network services opens up great opportunities for various kinds of knowledge-based intelligence activities which require tracking of real-time events. In a sense, visualizations in combination with analytical processes could be a viable method for such tasks because it can be used to analyze the sheer amounts of text streams. However, data analysts and visualization experts often face grand challenges stemming out of the ill-defined concept of event and various kinds of textual data. As a result, we have few guidelines on how to build successful visual analysis tools that can handle specific event types and diverse textual data sources. Our goal is to take the first step towards answering the question by organizing insights from prior research studies on event detection and visual analysis. In the scope of this report, we summarize the evolution of event detection in combination with visual analysis over the past 14 years and provide an overview of the state-of-the-art methods. Our investigation sheds light on various kinds of research areas that can be the most beneficial to the field of visual text event analytics.</dcterms:abstract>
    <dc:contributor>Wanner, Franz</dc:contributor>
    <dc:creator>Kwon, Bum Chul</dc:creator>
    <dc:creator>Weiler, Andreas</dc:creator>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2015-02-24T14:48:23Z</dc:date>
    <dc:contributor>Keim, Daniel A.</dc:contributor>
    <dc:contributor>Kwon, Bum Chul</dc:contributor>
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    <dc:creator>Jäckle, Dominik</dc:creator>
    <dcterms:issued>2014</dcterms:issued>
    <dcterms:title>State-of-the-Art Report of Visual Analysis for Event Detection in Text Data Streams</dcterms:title>
    <dc:creator>Keim, Daniel A.</dc:creator>
    <dc:creator>Wanner, Franz</dc:creator>
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