@inproceedings{Wanner2012Topic-26415,
  year={2012},
  title={Topic Tracker : Shape-based Visualization for Trend and Sentiment Tracking in Twitter},
  booktitle={Task-Driven Analysis of Social Media : The 2nd Workshop on Interactive Visual Text Analytics. Part of the VisWeek 2012, October 14 - 19, 2012, Seattle},
  author={Wanner, Franz and Weiler, Andreas and Schreck, Tobias}
}

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    <dcterms:title>Topic Tracker : Shape-based Visualization for Trend and Sentiment Tracking in Twitter</dcterms:title>
    <dcterms:issued>2012</dcterms:issued>
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    <dc:creator>Schreck, Tobias</dc:creator>
    <dc:contributor>Schreck, Tobias</dc:contributor>
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    <dc:creator>Weiler, Andreas</dc:creator>
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    <dc:creator>Wanner, Franz</dc:creator>
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    <dc:contributor>Wanner, Franz</dc:contributor>
    <dc:contributor>Weiler, Andreas</dc:contributor>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-03-28T10:31:37Z</dc:date>
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    <dcterms:abstract xml:lang="eng">In recent years there has been a continuous development of social media services on the web. Unprecedented success and active usage of these services result in massive amounts of user-generated data. Visual representation of these large amounts of unevenly distributed time series data is a challenging task, especially while preserving access to individual data points. Our hypothesis is that shape-based visual representations have advantages over established time series compression visualizations like Two-Tone Pseudo Coloring or line graphs. In this paper we present a shape-based visualization for trend and sentiment tracking of user-defined topics in the Twitter data stream. We use glyphs to visualize the appearance and sentiment of tweets on a timeline and enable analysts to keep track of the trend of their defined topic and the corresponding sentiment expressed by the Twitter users.</dcterms:abstract>
    <dcterms:bibliographicCitation>Vortrag gehalten bei: Task-Driven Analysis of Social Media : The 2nd Workshop on Interactive Visual Text Analytics. Part of the VisWeek 2012, October 14-19, 2012, Seattle</dcterms:bibliographicCitation>
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