An Analysis of Text Functions in Information Visualization

2025-07-16

AI Summary

Text functionality in information visualization lacks systematic scholarly investigation, resulting in a significant theory–practice gap. To address this, we conducted an empirical analysis of 120 real-world visualization cases and 804 textual elements, establishing a fine-grained taxonomy of text functions comprising ten core functional categories and four high-level design strategies. Our study uncovers three previously undocumented phenomena: rhetorical titling, multifunctional reuse of text, and text-based substitution for visual encoding—thereby extending theoretical understanding of text’s roles in data labeling, expressive augmentation, and narrative construction. The resulting framework advances the analytical foundations of text in visualization and provides designers with an actionable, function-driven design guide. This work significantly enhances both the theoretical rigor and practical effectiveness of textual usage in information visualization. (136 words)

Technology Category

• Data Mining & Knowledge Management: Data Visualization & Summarization
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Computer Vision: Visual Reasoning & Symbolic Representations

Application Category

• Web Mining and Content Analysis: Web data visualization
• User Modeling, Personalization and Recommendation: Personalized content ranking and presentation
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

Text is an integral but understudied component of visualization design. Although recent studies have examined how text elements (e.g., titles and annotations) influence comprehension, preferences, and predictions, many questions remain about textual design and use in practice. This paper introduces a framework for understanding text functions in information visualizations, building on and filling gaps in prior classifications and taxonomies. Through an analysis of 120 real-world visualizations and 804 text elements, we identified ten distinct text functions, ranging from identifying data mappings to presenting valenced subtext. We further identify patterns in text usage and conduct a factor analysis, revealing four overarching text-informed design strategies: Attribution and Variables, Annotation-Centric Design, Visual Embellishments, and Narrative Framing. In addition to these factors, we explore features of title rhetoric and text multifunctionality, while also uncovering previously unexamined text functions, such as text replacing visual elements. Our findings highlight the flexibility of text, demonstrating how different text elements in a given design can combine to communicate, synthesize, and frame visual information. This framework adds important nuance and detail to existing frameworks that analyze the diverse roles of text in visualization.

Problem

• Understanding text functions in visualization design
• Analyzing patterns in text usage strategies
• Exploring unexamined text roles like visual replacement

Innovation

• Framework for text functions in visualizations
• Analysis of 120 visualizations and 804 texts
• Identified four text-informed design strategies