The influence of font scale on semantic expression of word cloud

Abstract

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.