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Text and Data Mining (TDM) in Research: Applications and Tools – Mar. 3, 2022
Session Description
March 3, 2022 @ 3:30 pm - 5:00 pm
Text and data mining is the science of extracting information, identifying patterns, or knowledge from large bodies of text, in the case of text mining, or data, in the case of data mining*. Researchers have used text and data mining in various ways such as abstract screening for knowledge synthesis, determining changes in human languages, and generally detecting patterns, trends and drawing new conclusions from large datasets.
The Centre for Research Innovation & Support (CRIS) in collaboration with the University of Toronto Libraries (UTL) is hosting a session on text and data mining in research. This session will highlight how various researchers apply text and data mining methods to their research. Researchers will share their knowledge and experience on the application of text and data mining tools in analyzing large datasets, and showcase examples to illustrate the potential utility of these tools for different research use cases.
*Definition adapted from Universityof Toronto Libraries website
Panelists:
- Kelly Schultz (Moderator) - Data Visualization Librarian, Lead – Text and Data Mining, from the Map and Data Library, University of Toronto
- Dr. Michelle Alexopoulos - Professor in the department of Economics at the University of Toronto.
- Dr. Frank Rudzicz - Associate Professor, Department of Computer Science at the University of Toronto
Learning Objectives
By the end of the session, participants will better be able to:
- Identify various text and data mining tools that U of T researchers have used in their research.
- Learn how other researchers have incorporated text and data mining methods in their methods
- Articulate the potential benefits and common challenges of using text and data mining methods for conducting research.
- Access U of T resources and supports for text and data mining.
Additional Information
Click to download Prof. Michelle Alexopolous Slides
Click to download Prof. Frank Rudzicz Slides
Click to download Additional Library Resources Slides
For link to the session recording (requires UTORid) click here.
