Quantity estimation in visualizations of tagged text

Authors:
Michael A. Correll;Eric C. Alexander;Michael Gleicher
Affiliations:
University of Wisconsin - Madison, Madison, Wisconsin, USA;University of Wisconsin - Madison, Madison, Wisconsin, USA;University of Wisconsin - Madison, Madison, Wisconsin, USA
Venue:
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Year:
2013

Citing 6
Cited 0

Discovering interesting usage patterns in text collections: integrating text mining with visualization

Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Crowdsourcing user studies with Mechanical Turk

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Who are the crowdworkers?: shifting demographics in mechanical turk

CHI '10 Extended Abstracts on Human Factors in Computing Systems
Visualization of text streams: a survey

KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Comparing averages in time series data

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Exploring collections of tagged text for literary scholarship

EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization

Quantified Score

Hi-index	0.01

Visualization

Abstract

A valuable task in text visualization is to have viewers make judgments about text that has been annotated (either by hand or by some algorithm such as text clustering or entity extraction). In this work we look at the ability of viewers to make judgments about the relative quantities of tags in annotated text (specifically text tagged with one of a set of qualitatively distinct colors), and examine design choices that can improve performance at extracting statistical information from these texts. We find that viewers can efficiently and accurately estimate the proportions of tag levels over a range of situations; however accuracy can be improved through color choice and area adjustments.