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An Evaluation of Semantically Grouped Word Cloud Designs

机译:对语义分组词云设计的评估

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摘要

Word clouds continue to be a popular tool for summarizing textual information, despite their well-documented deficiencies for analytic tasks. Much of their popularity rests on their playful visual appeal. In this paper, we present the results of a series of controlled experiments that show that layouts in which words are arranged into semantically and visually distinct zones are more effective for understanding the underlying topics than standard word cloud layouts. White space separators and/or spatially grouped color coding led to significantly stronger understanding of the underlying topics compared to a standard Wordle layout, while simultaneously scoring higher on measures of aesthetic appeal. This work is an advance on prior research on semantic layouts for word clouds because that prior work has either not ensured that the different semantic groupings are visually or semantically distinct, or has not performed usability studies. An additional contribution of this work is the development of a dataset for a semantic category identification task that can be used for replication of these results or future evaluations of word cloud designs.
机译:尽管他们对分析任务的良好缺陷,Word云继续成为概括文本信息的流行工具。他们的大部分受欢迎程度都依赖于他们俏皮的视觉上诉。在本文中,我们介绍了一系列受控实验的结果,该结果表明,在语义上和视觉上的区域中排列单词的布局对于理解底层主题比标准字云布局更有效。与标准的Wordle布局相比,白色空间分离器和/或空间分组的颜色编码导致对潜在主题的了解显着更强,同时对美学吸引力的测量同时得分。这项工作是关于Word云的语义布局的先前研究的进步,因为未确保不同的语义分组在视觉上或语义上独立,或者没有执行可用性研究。这项工作的额外贡献是开发用于语义类别标识任务的数据集,可用于复制这些结果或Word云设计的未来评估。

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