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Emosaic: Visualizing Affective Content of Text at Varying Granularity

  • 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 theThis 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.zeige mehrzeige weniger

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Metadaten
Verfasserangaben:Philipp Geuder, Marie-Claire Leidinger, Martin von Lupin, Marian DörkORCiD, Tobias SchröderORCiDGND
DOI:https://doi.org/10.48550/arXiv.2002.10096
Titel des übergeordneten Werkes (Englisch):arxiv.org
Verlag:Cornell University
Dokumentart:Arbeitspapier
Sprache:Englisch
Datum der Veröffentlichung (online):10.08.2023
Jahr der Erstveröffentlichung:2020
Datum der Freischaltung:17.08.2023
Freies Schlagwort / Tag:Farbzuweisung; Farbübersetzung
GND-Schlagwort:Mensch-Maschine-Kommunikation; Digital; Visualisierung; Text; Emotion; Farbe
Aufsatznummer:arXiv:2002.10096
Seitenzahl:9
Fachbereiche und Zentrale Einrichtungen:FB4 Design
Forschungs- und An-Institute / Inst. für angewandte Forschung Urbane Zukunft (IaF)
DDC-Klassifikation:000 Informatik, Informationswissenschaft, allgemeine Werke / 000 Informatik, Wissen, Systeme
Lizenz (Deutsch):License LogoCreative Commons - CC BY - Namensnennung 4.0 International
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