Finding What to Read  Visual Text Analytics Tools and Techniques - Christopher Collins
Channel: BocoupLLC
Date: 2016-05-13

Abstract:

Text is one of the most prominent forms of open data available, from social media to legal cases. Text visualizations are often critiqued for not being useful, for being unstructured and presenting data out of context (think: word clouds). In this talk, Chris will argue that we should not expect them to be a replacement for reading. He will briefly discuss the close/distant reading debate then focus on where text visualization can be useful: hypothesis generation and guiding investigation. Text visualization can help someone form questions about a large text collection, then drill down to investigate through targeted reading of the underlying source texts.

Chris will also discuss the design challenges which, while common across visualization, are particularly important with text (e.g. legibility, label fitting, finding appropriate levels of ‘zoom’) as well as what are interesting open challenges in this field.

About our Speaker:

Christopher Collins is the Canada Research Chair in Linguistic Information Visualization and an Assistant Professor of Computer Science at the University of Ontario Institute of Technology (UOIT). His research focus is interdisciplinary, combining information visualization and human-computer interaction with natural language processing to address the challenges of information management and the problems of information overload. His work has been published in many venues including IEEE Transactions on Visualization and Computer Graphics, and has been featured in popular media such as the Toronto Star and the New York Times Magazine. Collins received his Ph.D. in Computer Science from the University of Toronto.

More about Chris: http://vialab.science.uoit.ca/