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