Bei Yu from Syracuse University, USA will give a keynote speech at INRA 2016.
About the talk:
News Recommendation and Analytics in a Polarizing World
In recent years, the concerns over public opinion polarization and misinformation spread are rapidly increasing, particularly on politics and science topics. Online social media and personalized search and recommender systems have been warned as a contributing factor for segregating opinions by creating the so-called "echo-chambers" and "filter bubbles". Could we change the recommender system for healthier opinion exchange? Would designing algorithms to diversify opinions in recommended items help alleviate the problem? Drawing on theoretical and empirical studies from multiple disciplines, this talk will discuss the challenge of news recommendation and analytics in the polarizing world, and how interdisciplinary research like natural language processing and cognitive psychology might be able to help design and evaluate future recommender systems.
About the speaker:
Bei Yu
Associate Professor at School of Information Studies
Syracuse University, USA
byu@syr.edu
Bei Yu is a Katchmar-Wilhelm Associate Professor of Information Studies at Syracuse University. Before joining SU she was a postdoctoral fellow at Kellogg School of Management, Northwestern University. She received her PhD in Library and Information Science in 2006 from the University of Illinois at Urbana-Champaign. She also holds Master's and Bachelor's degrees in Computer Science. Her research focuses on text mining, especially sentiment classification and opinion mining, for social science research and digital humanities. Bei Yu has given invited talks on the analysis of language, gender, and opinion differences in political speeches and documents. In 2009 she was the co-chair of the First International Workshop on Topic-Sentiment Analysis for Mass Opinion Measurement in Hong Kong, organized in conjunction with the 18th ACM Conference on Information and Knowledge Management.
