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Discover Text Software Training: Unlock the Power of Text
Friday, February 4, 9-1
1 a.m.
Location: Frances Searle Building, Room 1.459 (SONIC Conference Room)
Discover Text Software Training: Unlock the Power of Text: A PhD-holding Political Scientist, Stu knows the importance of easy to use, powerful, text analytic software. As founder of a technology start up (http://texifter.com) and the QDAP labs (http://www.umass.edu/qdap), Stu’s work advances text mining and natural language processing research. His software trainings link these worlds via straightforward and easy to understand explanations of software features that can be tailored for all experience levels and project types.
Dr. Stuart W. Shulman is founder & CEO of Texifter, LLC and an Assistant Professor of Political Science at the University of Massachusetts Amherst. He is the founding Director of the Qualitative Data Analysis Program (QDAP) at the University of Pittsburgh and at UMass Amherst, as well as Associate Director of the National Center for Digital Government.
Stuart Shulman SONIC Speaker Series
Stuart Shulman presents “Measuring Validity in Annotation” Friday, February 4, 2011.Tools for reviewing, coding, and retrieving text found in qualitative data analysis packages carry with them no particular attributes for ensuring the reliability or validity of the recorded observations. Based on more than 10 years of multidisciplinary experience doing qualitative research, this presentation guides researchers through aspects of coder validity and reliability.
Dr. Stuart W. Shulman is founder & CEO of Texifter, LLC and an Assistant Professor of Political Science at the University of Massachusetts Amherst. He is the founding Director of the Qualitative Data Analysis Program (QDAP) at the University of Pittsburgh and at UMass Amherst, as well as Associate Director of the National Center for Digital Government.
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Measuring Validity in Annotation
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Local Model of Scientific Collaboration in Developing Nation
A region specific study, located in the Middle East, on the scientific collaboration of physicists, who are based in Iran, across multiple disciplines was recently done a few months ago. Analyzing the network’s basic properties, betweenness, diamater, etc., the local model is then compared to the global model of scientific collaboration to discover how a developing region such as the Middle East can contribute to global scientific process statistically. However, what becomes striking is how the local model unexpectedly differs from the global model. For example, despite the fact that the diameter of Iran’s physicists network is much smaller, resulting from a low diversity of information and disciplines, the physicists are reluctant to collaborate.