Details
| Original language | English |
|---|---|
| Article number | 9222553 |
| Pages (from-to) | 1139-1148 |
| Number of pages | 10 |
| Journal | IEEE Transactions on Visualization and Computer Graphics |
| Volume | 27 |
| Issue number | 2 |
| Publication status | Published - 15 Feb 2021 |
| Externally published | Yes |
Abstract
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.
Keywords
- Argumentation Visualization, Close and Distant Reading, Coordinated and Multiple Views, Glyph-based Techniques, Information Visualization, Text Analysis, Text and Document Data, Tree-based Visualization, User Interfaces, Visual Analytics
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Computer Science(all)
- Signal Processing
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Computer Science(all)
- Computer Graphics and Computer-Aided Design
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In: IEEE Transactions on Visualization and Computer Graphics, Vol. 27, No. 2, 9222553, 15.02.2021, p. 1139-1148.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Visual Analysis of Argumentation in Essays
AU - Kiesel, Dora
AU - Riehmann, Patrick
AU - Wachsmuth, Henning
AU - Stein, Benno
AU - Froehlich, Bernd
PY - 2021/2/15
Y1 - 2021/2/15
N2 - 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.
AB - 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.
KW - Argumentation Visualization
KW - Close and Distant Reading
KW - Coordinated and Multiple Views
KW - Glyph-based Techniques
KW - Information Visualization
KW - Text Analysis
KW - Text and Document Data
KW - Tree-based Visualization
KW - User Interfaces
KW - Visual Analytics
UR - http://www.scopus.com/inward/record.url?scp=85097127137&partnerID=8YFLogxK
U2 - 10.1109/TVCG.2020.3030425
DO - 10.1109/TVCG.2020.3030425
M3 - Article
C2 - 33048728
AN - SCOPUS:85097127137
VL - 27
SP - 1139
EP - 1148
JO - IEEE Transactions on Visualization and Computer Graphics
JF - IEEE Transactions on Visualization and Computer Graphics
SN - 1077-2626
IS - 2
M1 - 9222553
ER -