Conference Paper/Proceeding/Abstract 806 views 259 downloads
Emoji and Chernoff - A Fine Balancing Act or are we Biased?
Ricardo Colasanti,
Rita Borgo,
Mark Jones 
2019 IEEE Pacific Visualization Symposium (PacificVis), Pages: 102 - 111
Swansea University Author:
Mark Jones
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PDF | Accepted Manuscript
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DOI (Published version): 10.1109/PacificVis.2019.00020
Abstract
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...
| Published in: | 2019 IEEE Pacific Visualization Symposium (PacificVis) |
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| ISBN: | 978-1-5386-9227-1 978-1-5386-9226-4 |
| ISSN: | 2165-8765 2165-8773 |
| Published: |
Bangkok, Thailand
2019
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa48170 |
| Abstract: |
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. |
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| Start Page: |
102 |
| End Page: |
111 |