Word clouds are widely used for non-analytic purposes, such as introducing a topic to students, or creating a gift with personally meaningful text. Surveys show that users prefer tools that yield word clouds with a stronger emotional impact. Fonts and color palettes are powerful typographical signals that may determine this impact. Typically, these signals are assigned randomly, or expected to be chosen by the users. We present an affect-aware font and color palette selection methodology that aims to facilitate more informed choices. We infer associations of fonts with a set of eight affects, and evaluate the resulting data in a series of user studies both on individual words as well as in word clouds. Relying on a recent study to procure affective color palettes, we carry out a similar user study to understand the impact of color choices on word clouds. Our findings suggest that both fonts and color palettes are powerful tools contributing to the affects evoked by a word cloud. The experiments further confirm that the novel datasets we propose are successful in enabling this. We also find that, for the majority of the affects, both signals need to be congruent to create a stronger impact. Based on this data, we implement a prototype that allows users to specify a desired affect and recommends congruent fonts and color palettes for the word.

中文翻译：

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情感感知词云

词云被广泛用于非分析目的，例如向学生介绍主题，或创建带有个人意义文本的礼物。调查显示，用户更喜欢产生具有更强情感影响的词云的工具。字体和调色板是强大的印刷信号，可以确定这种影响。通常，这些信号是随机分配的，或者预期由用户选择。我们提出了一种影响感知字体和调色板选择方法，旨在促进更明智的选择。我们推断字体与一组八种影响的关联，并在一系列关于单个单词和词云的用户研究中评估结果数据。依靠最近的一项研究来采购情感调色板，我们进行了类似的用户研究，以了解颜色选择对词云的影响。我们的研究结果表明，字体和调色板都是强大的工具，有助于产生由词云引起的影响。实验进一步证实，我们提出的新数据集成功地实现了这一点。我们还发现，对于大多数影响，两个信号需要一致才能产生更强的影响。基于这些数据，我们实现了一个原型，允许用户指定所需的效果并为单词推荐一致的字体和调色板。对于大多数影响，两个信号需要一致才能产生更强的影响。基于这些数据，我们实现了一个原型，允许用户指定所需的效果并为单词推荐一致的字体和调色板。对于大多数影响，两个信号需要一致才能产生更强的影响。基于这些数据，我们实现了一个原型，允许用户指定所需的效果并为单词推荐一致的字体和调色板。