Emoji and Chernoff – A Fine Balancing Act or are we Biased?

Ric Colasanti, Rita Borgo, Mark W. Jones

Crynodeb

We seek to answer the question on whether different geometrical attributes within a glyph can bias interpretation of data. We focus on a specific visual encoding, the Emoji, and evaluate its effectiveness at encoding multidimensional features. Given the anthropomorphic nature of the encoding we seek to quantify the amount of bias the encoding itself introduces, and use this to balance the Emoji glyph to remove that bias. We perform our analysis by comparing Emoji with Chernoff faces, of which they can be seen as direct descendant. Results shed light on how this new approach of feature tuning in glyph design can influence overall effectiveness of novel multidimensional encodings.

Deunyddiau Ffynhonnell

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DOI

10.1109/PacificVis.2019.00020
https://dx.doi.org/10.1109/PacificVis.2019.00020

Enwi

Ric Colasanti, Rita Borgo, Mark W. Jones. Emoji and Chernoff – A Fine Balancing Act or are we Biased? In 2019 IEEE Pacific Visualization Symposium (PacificVis), Bangkok 2019. pp. 102-111. https://doi.org/10.1109/PacificVis.2019.00020

Bibtex

@INPROCEEDINGS{GlyphBalancing, 
author={R. {Colasanti} and R. {Borgo} and M. W. {Jones}}, 
booktitle={2019 IEEE Pacific Visualization Symposium (PacificVis)}, 
title={Emoji and Chernoff - A Fine Balancing Act or are we Biased?}, 
year={2019}, 
pages={102-111}, 
doi={10.1109/PacificVis.2019.00020}, 
ISSN={2165-8773}, 
month={April},}