  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.
