Publication type.
Legend:
0 = Uncategorized
1 = Conference paper
2 = Journal article
3 = Manuscript
4 = Report
5 = Book
6 = Book section
publication_types = [“1”]
Publication name and optional abbreviated version.
publication = “In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, ACM.” publication_short = “In CHI”
Abstract and optional shortened version.
abstract = “We propose a visualization technique, Du Bois wrapped bar chart, inspired by work of W.E.B Du Bois. Du Bois wrapped bar charts enable better large-to-small bar comparison by wrapping large bars over a certain threshold. We first present two crowdsourcing experiments comparing wrapped and standard bar charts to evaluate (1) the benefit of wrapped bars in helping participants identify and compare values; (2) the characteristics of data most suitable for wrapped bars. In the first study (n=98) using real-world datasets, we find that wrapped bar charts lead to higher accuracy in identifying and estimating ratios between bars. In a follow-up study (n=190) with 13 simulated datasets, we find participants were consistently more accurate with wrapped bar charts when certain category values are disproportionate as measured by entropy and H-spread. Finally, in an in-lab study, we investigate participants’ experience and strategies, leading to guidelines for when and how to use wrapped bar charts.” abstract_short = “”
Is this a selected publication? (true/false)
selected = false
Projects (optional).
Associate this publication with one or more of your projects.
Simply enter your project’s folder or file name without extension.
E.g. projects = ["deep-learning"]
references
content/project/deep-learning/index.md
.
Otherwise, set projects = []
.
projects = []
Links (optional).
url_pdf = “https://dl.acm.org/doi/abs/10.1145/3313831.3376365” url_preprint = “https://arxiv.org/abs/2001.03271” url_code = “https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3313831.3376365&file=pn3825aux.zip&download=true” url_dataset = “” url_project = “https://medium.com/multiple-views-visualization-research-explained/visualizing-categorical-data-with-disproportionate-values-using-du-bois-wrapped-bar-charts-7dd9e4901fa6” url_slides = “” url_video = “https://www.youtube.com/watch?v=j0qykZO7YKU” url_poster = “” url_source = “”
Custom links (optional).
Uncomment line below to enable. For multiple links, use the form [{...}, {...}, {...}]
.
url_custom = [{name = “Custom Link”, url = “http://example.org”}]
Digital Object Identifier (DOI)
doi = “”
Does this page contain LaTeX math? (true/false)
math = false
Featured image
To use, add an image named featured.jpg/png
to your page’s folder.
[image] # Caption (optional) # caption = “Image credit: Unsplash”
# Focal point (optional) # Options: Smart, Center, TopLeft, Top, TopRight, Left, Right, BottomLeft, Bottom, BottomRight focal_point = “” +++