As HCI, Machine Learning and Data Mining have become more integrated we’ve had the opportunity to rethink the way people interact with text. The use of new text mining techniques has allowed us better appreciate how textual information is consumed and produced. Everything from news articles to legislative materials, to computer programs, can not only be better modeled through the lens of text mining, but we can create entirely new experiences. I’ll touch on some recent work in my group on personalization, program generation, visualizations for distributed language models, and applications of meme propagation to laws and why I think it’s exciting times for the intersection of text mining and HCI.
Eytan Adar is an Associate Professor in the School of Information & Computer Science and Engineering at the University of Michigan (though he’s currently on sabbatical at Adobe and UW). He works broadly at the intersection of HCI and IR/Data Mining and ranges from empirical studies of large-scale online behaviors to building new systems, tools and methods. He completed his doctoral work in the Computer Science at the University of Washington and has a Masters and Bachelors degree from MIT. Before going back for his PhD, Eytan was a researcher at HP Labs and Xerox PARC for a number of years (spinning out a company called Outride somewhere in there). Eytan is co-founder of ICWSM and has served as general chair for ICWSM and WSDM. His website is at http://www.cond.org