Our online behaviour is far from virtual–it extends our offline lives. Much social media research has identified the positive opportunities of using social media; for example, how people use social media to form support groups online, participate in political uprising, raise money for charities, extend teaching and learning outside the classroom, etc. However, mirroring offline experiences, we have also seen social media being used to spread propaganda and misinformation, recruit terrorists, live stream criminal activities, reinforce echo chambers by politicians, and perpetuate hate and oppression (such as racist, sexist, homophobic, and anti-Semitic behaviour).
THIS IS PART 2 OF THIS WORKSHOP, PLEASE MAKE SURE TO SIGN-UP FOR PART 1.
Workshop Facilitator
Dr. Stu Shulman, Texifter (USA)
Workshop Details
Participate in this workshop to learn how to build custom machine classifiers for sifting social media data. The topics covered include how to:
DiscoverText is designed specifically for collecting and cleaning up messy Twitter data streams. Use basic research measurement tools to improve human and machine performance classifying Twitter data over time. The workshop covers how to reach and substantiate inferences using a theoretical and applied model informed by a decade of interdisciplinary, National Science Foundation-funded research into the text classification problem.
Participants will learn how to apply “CoderRank” in machine-learning. Just as Google said not all web pages are created equal, links on some pages rank higher than others, Dr. Shulman argues not all human coders are created equal; the accuracy of observations by some coders on any task invariably rank higher than others. The major idea of the workshop is that when training machines for text analysis, greater reliance should be placed on the input of those humans most likely to create a valid observation. Texifter proposed a unique way to recursively validate, measure, and rank humans on trust and knowledge vectors, and called it CoderRank.
Instructor’s Bio
Dr. Stuart W. Shulman is founder & CEO of Texifter. He was a Research Associate Professor of Political Science at the University of Massachusetts Amherst and the founding Director of the Qualitative Data Analysis Program (QDAP) at the University of Pittsburgh and at UMass Amherst. Dr. Shulman is Editor Emeritus of the Journal of Information Technology & Politics, the official journal of Information Technology & Politics section of the American Political Science Association.
