Anchors and ratios to quantify and explain y-axis distortion effects in graphs.

Authors

Denis Cousineau (ORCID: https://orcid.org/0000-0001-5908-0402)
Shuo Zang (ORCID: https://orcid.org/0009-0000-4387-8145)

Institutions

University of Ottawa (CA)

Publication Details

Journal: Journal of Experimental Psychology Learning Memory and Cognition
Published: 2025-02-18
DOI: https://doi.org/10.1037/xlm0001454
Citations: 1
Primary Topic: Advanced Graph Neural Networks
Type: article
Field-Weighted Citation Impact: 2.48

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article

Anchors and ratios to quantify and explain y-axis distortion effects in graphs.

Denis Cousineau, Shuo Zang

Feb 18, 2025

1 citations

Journal of Experimental Psychology Learning Memory and Cognition

Advanced Graph Neural Networks

2.48

article

Anchors and ratios to quantify and explain y-axis distortion effects in graphs.

Denis Cousineau, Shuo Zang

February 18, 2025article en

1 citations

Abstract

No abstract available for this paper.

Journal of Experimental Psychology Learning Memory and CognitionVol. 51(9)

University of Ottawa (CA)

Openalex Percentile: Top 12%

Advanced Graph Neural Networks

2.48

DOI Source OpenAlex

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Anchors and ratios to quantify and explain y-axis distortion effects in graphs. — Denis Cousineau, Shuo Zang · Journal of Experimental Psychology Learning Memory and Cognition (2025) | TGRS Research Map | TGRS