IEEE Trans Vis Comput Graph. 2021 Feb;27(2):1139-1148. doi: 10.1109/TVCG.2020.3030425. Epub 2021 Jan 28.
This paper presents a visual analytics system for exploring, analyzing and comparing argument structures in essay corpora. We provide an overview of the corpus by a list of ArguLines which represent the argument units of each essay by a sequence of glyphs. Each glyph encodes the stance, the depth and the relative position of an argument unit. The overview can be ordered in various ways to reveal patterns and outliers. Subsets of essays can be selected and analyzed in detail using the Argument Unit Occurrence Tree which aggregates the argument structures using hierarchical histograms. This hierarchical view facilitates the estimation of statistics and trends concerning the progression of the argumentation in the essays. It also provides insights into the commonalities and differences between selected subsets. The text view is the necessary textual basis to verify conclusions from the other views and the annotation process. Linking the views and interaction techniques for visual filtering, studying the evolution of stance within a subset of essays and scrutinizing the order of argumentative units enable a deep analysis of essay corpora. Our expert reviews confirmed the utility of the system and revealed detailed and previously unknown information about the argumentation in our sample corpus.
本文提出了一种用于探索、分析和比较论文语料库中论点结构的可视分析系统。我们通过一个由 ArguLines 组成的列表提供了语料库的概述，这些 ArguLines 通过一系列符号来表示每篇论文的论点单元。每个符号都对论点单元的立场、深度和相对位置进行编码。概述可以通过各种方式进行排序，以揭示模式和异常值。使用论点单元出现树可以选择和详细分析子集的论文，该树使用层次直方图对论点结构进行聚合。这种层次视图有助于估计与论文中论证进展有关的统计数据和趋势。它还提供了关于所选子集之间的共性和差异的见解。文本视图是从其他视图验证结论和注释过程的必要文本基础。链接视图和用于视觉过滤的交互技术、研究一个子集内立场的演变以及仔细研究论证单元的顺序，可以对论文语料库进行深入分析。我们的专家评论证实了该系统的实用性，并揭示了我们样本语料库中论证的详细和以前未知的信息。
