<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>1548</id>
    <completedYear/>
    <publishedYear>2016</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>263</pageFirst>
    <pageLast>266</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>bookpart</type>
    <publisherName>nisaba verlag</publisherName>
    <publisherPlace>Duisburg</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2017-05-23</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Emosaic – Visualisierung von Emotionen in Texten durch Farbumwandlung zur Analyse und Exploration</title>
    <abstract language="deu">Das computergestützte Extrahieren und Visualisieren von Emotionen in Texten ist eine etablierte Technik des “Distant Reading”. Die generelle Stimmung eines Textes kann schnell erfasst werden ohne den gesamten Text lesen zu müssen. Da Emotionen sehr komplex und die Eigenschaften zwischen verschiedenen Emotionen fließend sind, ist die visuelle Charakterisierung von Emotionen schwierig. Wir stellen Emosaic  vor, ein Online-Tool welches Emotionen aus benutzerdefinierten Texten filtert und durch systematische und nachvollziehbare Farbumwandlung zur Exploration und Analyse innerhalb einer interaktiven Visualisierung bereitstellt. Die durch drei Dimensionen beschreibbaren Emotionen werden dabei in klar definierte Farbparameter übersetzt. Ein von uns entwickelter öffentlich zugänglicher Web- Prototyp ( vgl. Geuder et al. 2014-) zeigt anhand interaktiver Visualisierungen erste Analyse- und Explorationsmöglichkeiten dieser Methode.</abstract>
    <parentTitle language="deu">DHd 2016 : Modellierung - Vernetzung - Visualisierung : die Digital Humanities als fächerübergreifendes Forschungsparadigma : Konferenzabstracts : Universität Leipzig, 7. bis 12. März 2016</parentTitle>
    <identifier type="isbn">978-3-941379-05-3</identifier>
    <author>Martin von Lupin</author>
    <author>Philipp Geuder</author>
    <author>Marie-Claire Leidinger</author>
    <author>Tobias Schröder</author>
    <author>Marian Dörk</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Geisteswissenschaften</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Digital</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Visualisierung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Text</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Emotion</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Farbe</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Farbzuweisung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Farbübersetzung</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Informationswissenschaft, allgemeine Werke</collection>
    <collection role="institutes" number="">Inst. für angewandte Forschung Urbane Zukunft (IaF)</collection>
  </doc>
  <doc>
    <id>3158</id>
    <completedYear/>
    <publishedYear>2020</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber>9</pageNumber>
    <edition/>
    <issue/>
    <volume/>
    <type>workingpaper</type>
    <publisherName>Cornell University</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2023-08-10</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Emosaic: Visualizing Affective Content of Text at Varying Granularity</title>
    <abstract language="eng">This paper presents Emosaic, a tool for visualizing the emotional tone of text documents, considering multiple dimensions of emotion and varying levels of semantic granularity. Emosaic is grounded in psychological research on the relationship between language, affect, and color perception. We capitalize on an established three-dimensional model of human emotion: valence (good, nice vs. bad, awful), arousal (calm, passive vs. exciting, active) and dominance (weak, controlled vs. strong, in control). Previously, multi-dimensional models of emotion have been used rarely in visualizations of textual data, due to the perceptual challenges involved. Furthermore, until recently most text visualizations remained at a high level, precluding closer engagement with the deep semantic content of the text. Informed by empirical studies, we introduce a color mapping that translates any point in three-dimensional affective space into a unique color. Emosaic uses affective dictionaries of words annotated with the three emotional parameters of the valence-arousal-dominance model to extract emotional meanings from texts and then assigns to them corresponding color parameters of the hue-saturation-brightness color space. This approach of mapping emotion to color is aimed at helping readers to more easily grasp the emotional tone of the text. Several features of Emosaic allow readers to interactively explore the affective content of the text in more detail; e.g., in aggregated form as histograms, in sequential form following the order of text, and in detail embedded into the text display itself. Interaction techniques have been included to allow for filtering and navigating of text and visualizations.</abstract>
    <parentTitle language="eng">arxiv.org</parentTitle>
    <identifier type="doi">10.48550/arXiv.2002.10096</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Philipp Geuder</author>
    <author>Marie-Claire Leidinger</author>
    <author>Martin von Lupin</author>
    <author>Marian Dörk</author>
    <author>Tobias Schröder</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Mensch-Maschine-Kommunikation</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Digital</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Visualisierung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Text</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Emotion</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Farbe</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Farbzuweisung</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>uncontrolled</type>
      <value>Farbübersetzung</value>
    </subject>
    <collection role="ddc" number="000">Informatik, Wissen, Systeme</collection>
    <collection role="institutes" number="">FB4 Design</collection>
    <collection role="institutes" number="">Inst. für angewandte Forschung Urbane Zukunft (IaF)</collection>
  </doc>
</export-example>
