D02 | Visual Analytics for Linguistic Representations

Prof. Miriam Butt, University of Konstanz
Email | Website

Miriam Butt

Prof. Daniel Weiskopf, University of Stuttgart
Email | Website

Daniel Weiskopf

Project D02

Dr. Christin Beck, University of Konstanz – EmailWebsite

Lukas Beiske, University of Konstanz – EmailWebsite

Within linguistics, the use of large sets of data via a combination of rule-based and stochastic methods is now standardly part of the analysis of language structure. However, though scatter plots, bar or pie charts, and trees as provided by R, for example, are standardly used, novel visual computation techniques have only just begun to be explored. The overall aim of this project is to evaluate whether visual analytics indeed represents a methodology that can yield improved results for linguistic research and to establish metrics for the evaluation of visual analytics approaches by conducting linguistically motivated case studies on historical data.

Research Questions

What visual variables and representations are most effective for which problems?

Which metrics for evaluation can be established?

What visual variables and representations are most effective for which problems?

Can visual analytic methods yield improved results within linguistic research?

Can we find linguistic patterns/insights we could not have found without visual analytics?

Can we find patterns/insights more quickly with visual analytics than without?

Fig. 1: Glyph visualization of dative subjects and semantic verb classes in Icelandic.

Publications

Error rendering list of publications

Project Group A

Models and Measures

 

Completed

 

Project Group B

Adaptive Algorithms

 

Completed

 

Project Group C

Interaction

 

Completed

 

Project Group D

Applications

 

Completed