Steffen Koch: Visual Text Analytics

Abstract

Text is language represented in a symbolic, visual way. It might seem cumbersome that someone seeks to find other visual representations for text or suggests them for text analysis. And, indeed, despite sayings such as "A picture is worth a thousand words", it is difficult to come up with a similarly expressive visual representation. Doing so would simply translate the text into another symbolic representation with the same complexity, which has to be learned as any other language, and nothing would be gained. (Additional) Visual representation of text therefore only makes sense for specific tasks, e.g., if aspects of interest can be extracted from text, if text can be summarized, or retrieved. In general, text visualization is a good method for scaling up tasks and/or if only specific characteristics of text and text documents are of interest. With the ever increasing amount of digital text produced by our society, it becomes more and more difficult to explore, find, and make sense of important information in large textual bodies. Here visualization and, in particular, approaches from the field of visual analytics offer viable solutions. This talk will discuss situations and tasks that can benefit from visual text analysis and present examples for a variety of application domains including social media analysis, analysis of scientific literature, and approaches for the digital humanities.

Organisational details

Visual Text Analytics
Wednesday, 28th February 2018
10:00 h
O27/2201

Biographic notes

Portrait of Dr Steffen Koch

Steffen Koch earned his doctorate degree in computer science from the University of Stuttgart, Germany, in 2012. He currently has a permanent position as a research associate at the Institute for Visualization and Interactive Systems at University of Stuttgart. His research interests comprise visualization in general, with foci on visual analytics for text/documents, visualization in the digital humanities, and interactive visualization support for data mining/machine learning.