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Activity Number: 353 - Visual Stories That Count!
Type: Contributed
Date/Time: Wednesday, August 5, 2020 : 10:00 AM to 2:00 PM
Sponsor: Section on Statistical Graphics
Abstract #313682
Title: Measuring the Significance of Text Source Using Visual Statistical Inference
Author(s): Mahbubul Majumder* and Jim Rogers
Companies: University of Nebraska at Omaha and University of Nebraska at Omaha
Keywords: visual inference; text data; data visualization; visual analytics
Abstract:

A combination of texts may represent the intrinsic pattern of a natural flow of tasks. An expert may observe the text data and identify the source of the text based on some pattern or meaning of the text. The question is how to detect whether the finding is statistically significant. In this paper we present a method to determine the statistical significance of text source using visual statistical inference procedure.


Authors who are presenting talks have a * after their name.

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