Understanding Bias in Perceiving Dimensionality Reduction Projections

Seoyoung Doh, Hyeon Jeon, Sungbok Shin, Ghulam Jilani Quadri, Nam Wook Kim +1 more
7/28/2025
cs.HCcs.LG

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Abstract

Selecting the dimensionality reduction technique that faithfully represents the structure is essential for reliable visual communication and analytics. In reality, however, practitioners favor projections for other attractions, such as aesthetics and visual saliency, over the projection's structural faithfulness, a bias we define as visual interestingness. In this research, we conduct a user study that (1) verifies the existence of such bias and (2) explains why the bias exists. Our study suggests that visual interestingness biases practitioners' preferences when selecting projections for analysis, and this bias intensifies with color-encoded labels and shorter exposure time. Based on our findings, we discuss strategies to mitigate bias in perceiving and interpreting DR projections.

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Cite this paper

@article{doh2025understanding,
  title  = {Understanding Bias in Perceiving Dimensionality Reduction Projections},
  author = {Seoyoung Doh and Hyeon Jeon and Sungbok Shin and Ghulam Jilani Quadri and Nam Wook Kim and Jinwook Seo},
  year   = {2025},
  eprint = {2507.20805},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2507.20805v1}
}

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