Wikipedia articles, tweets, and other forms of user-generated content (UGC) play an essential role in the experience of the average Web user. Outside the public eye, UGC has become equally indispensable as a source of world knowledge for systems and algorithms that help us make sense of big data. In this talk, I will demonstrate that UGC reflects the cultural diversity of its contributors to a previously unidentified extent and that this diversity has important implications for Web users and existing UGC-based technologies. Focusing on Wikipedia, I will show how UGC diversity can be extracted and measured using diversity mining algorithms and techniques from geographic information science. Finally, through two novel applications – Omnipedia and Atlasify – I will highlight the exciting potential for a new class of technologies enabled by the ability to harvest diverse perspectives from UGC.
Brent Hecht is an assistant professor of computer science and engineering at the University of Minnesota. With interests that lie at the intersection of human–computer interaction, geography, and big data, his research centers on the relationship between big data and human factors such as culture. A major focus of his work involves volunteered geographic information and its application in location-aware technologies.
Dr. Hecht received a Ph.D. in computer science from Northwestern University, a Master’s degree in geography from UC Santa Barbara, and dual Bachelor’s degrees in computer science and geography from Macalester College. He was a keynote speaker at WikiSym – the premiere conference on wikis and open collaboration – and has received awards for his research at top-tier publication venues in human-computer interaction and geography (e.g. ACM CHI, COSIT). He has collaborated with Google Research, Xerox PARC, and Microsoft Research, and his work been featured in the MIT Technology Review, New Scientist, AllThingsDigital, and various international TV, radio, and Internet outlets.
Wednesday Keynote session sponsored by IBM