Date of Award

2025

Degree Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science and Statistics

First Advisor

Shaun Wallace

Abstract

User perception of font size has influenced how researchers, typographers, and designers normalize fonts. To identify which font attributes contribute most to readers’ perceptions of font size across age groups and language backgrounds, we conduct a modified discrete choice experiment with crowdworkers. We develop new calibration and measurement methods to convert the size of font attributes in pixels to centimeters on a remote crowdworker’s screen. Results show that while character height was the most influential attribute, age and language background influence users’ perception differently. For participants with a Chinese language background, character weight was most important. Character weight and character spacing were more important for adults over 40 than for those under 40. Character Width was particularly more important for participants with a language background featuring long descenders, such as Hindi and Arabic. Our results provide the first evidence on personalizing font size normalization across age groups and language backgrounds.

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