Typeface size and weight and word location influence on relative size judgments in tag clouds

Khaldoon Dhou , Mirsad Hadzikadic , Mark Faust
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引用次数: 12

Abstract

This paper focuses on viewers’ perception of the relative size of words presented in tag clouds. Tag clouds are a type of visualization that displays the contents of a document as a cluster (cloud) of key words (tags) with frequency (importance) indicated by tag word features such as size or color, with variation of size within a tag cloud being the most common indicator of tag importance. Prior studies have shown that word size is the most influential factor of tag importance and tag memory. Systematic biases in relative size perception in tag clouds are therefore likely to have important implications for viewer understanding of tag cloud visualizations. Significant under- and over-perception of the relative size of tag words were observed, depending on the relative size ratio of the target tag words compared. The qualitative change in the direction of the estimation bias was predicted by a simple power-law model for size perception. This bias in relative size perception was modulated somewhat by a change to a bold typeface, but the typeface effect varied in a complex manner with the size and location of the tags. The results provide a first report of systematic biases in relative size judgment in tag clouds, suggest that, to a first approximation, simple power-law scaling models developed for simple displays containing 1–2 objects on a blank background, may be applicable to relative size judgments in complex tag clouds. The results may provide useful design guidance for tag cloud designers.

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标签云中字体大小、权重和单词位置对相对大小判断的影响
本文的重点是观察者对标签云中出现的单词的相对大小的感知。标签云是一种可视化类型,它将文档的内容显示为关键字(标签)的集群(云),其频率(重要性)由标签词特征(如大小或颜色)指示,标签云中大小的变化是标签重要性的最常见指标。先前的研究表明,单词大小是影响标签重要性和标签记忆的最重要因素。因此,标签云中相对大小感知的系统偏差可能对观众理解标签云可视化具有重要意义。根据所比较的目标标签词的相对大小比,观察到对标签词相对大小的显著低估和高估。通过尺寸感知的简单幂律模型预测了估计偏差方向的定性变化。这种相对大小感知的偏差在某种程度上受到了粗体字体变化的调节,但字体效果随着标签的大小和位置而以复杂的方式变化。该结果首次报告了标签云中相对大小判断的系统偏差,表明,在第一近似值下,为空白背景上包含1-2个对象的简单显示器开发的简单幂律缩放模型可能适用于复杂标签云中的相对大小判断。该结果可以为标签云设计者提供有用的设计指导。
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来源期刊
Journal of Visual Languages and Computing
Journal of Visual Languages and Computing 工程技术-计算机:软件工程
CiteScore
1.62
自引率
0.00%
发文量
0
审稿时长
26.8 weeks
期刊介绍: The Journal of Visual Languages and Computing is a forum for researchers, practitioners, and developers to exchange ideas and results for the advancement of visual languages and its implication to the art of computing. The journal publishes research papers, state-of-the-art surveys, and review articles in all aspects of visual languages.
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