Word cloud is a common text visualization technique. With the ability of presenting the keywords of a document in a direct way, it has been widely applied in many real-world situations. However, to better represent the main idea of a document, a critical aspect for word cloud design is to set an appropriate font size to facilitate semantic expression. In this paper, we explore the influence of font scale on semantic expression and evaluate font size of word cloud in a more systematic approach. To quantify semantic information of a document, we utilize an LDA ensemble-based method to support interactive selection of topics and obtain the semantics of documents in a scientific way. We conducted two pilot studies to decide important attributes of word clouds for the formal study. Through formal study 1, we find that the scale affects the semantic expression of word cloud, including accuracy, time and confidence in making judgments. In study 2, we explored different semantic expression patterns of word clouds under different document categories. Our findings aimed at optimizing the scale of word cloud and improving its semantic expressing ability.

中文翻译：

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字体尺度对词云语义表达的影响

词云是一种常见的文本可视化技术。由于能够以直接的方式呈现文档的关键字，它已被广泛应用于许多实际情况。但是，为了更好地表达文档的主要思想，词云设计的一个关键方面是设置合适的字体大小以方便语义表达。在本文中，我们探索字体比例对语义表达的影响，并以更系统的方法评估词云的字体大小。为了量化文档的语义信息，我们利用基于 LDA 集成的方法来支持主题的交互式选择，并以科学的方式获取文档的语义。我们进行了两项试点研究，以确定正式研究的词云的重要属性。通过正式学习1，我们发现尺度影响词云的语义表达，包括判断的准确性、时间和信心。在研究 2 中，我们探索了不同文档类别下词云的不同语义表达模式。我们的研究结果旨在优化词云的规模并提高其语义表达能力。