I now work as Data Scientist at LivingSocial at DC.
Fields of interest
Text Mining (esp. Sentiment Analysis), Computational Linguistics, Health Informatics, Social Media, Information Retrieval
Courses I taught
LIS690 208 Emerging Technologies: Web 2.0 & Social Media (communication theories, social network analysis, and CMC research) (offer in spring semester)
LIS630 Information Retrieval (Search engines and search system design patterns) (offer in fall semester)
LIS601 Information Seeking (Researches on Information seeking, needs and behavior) (offer every semester)
ning.yu at uky dot edu
Little Library Building
University of Kentucky
Lexington, KY 40506
I received my PhD in Information Science and Ph.D. minor in Cognitive Science with an emphasis on Computational Linguistics at Indiana University. I am interested in investigating the feasibility and efficiency of computational approaches, machine learning and NLP included, in understanding big data in the real world: from retrieving opinions in blog posts, to predicting ratings for online recipes, to understanding public attitudes towards suicide. I am also interested in network analysis and information visualization.
With access to endless user generate data on social media or via smart devices, researchers including myself have the power they never had before to observe how people behave in their everyday life and even to understand why they make certain decisions. In the past two years at UK, I have developed two interrelated "big data" research tracks : 1) Text mining with a focus on sentiment analysis. This track carries on my research from graduate school and focuses on general methodologies for automatically extracting sentiment, emotions or other categories from large amount of textual information; and 2) Web mining for suicide prevention. (Do you know suicide is the 10th leading cause of death in the U.S., claiming 38,285 lives in 2012?) By analyzing user generated content on the Web, this second track applies a broad range of Web mining technologies including those designed in the first track to understand the public perceptions and attitudes towards suicide, to identify possible new warning signs associated with suicide, and to evaluate the effectiveness of suicide prevention programs/campaigns.
"Dance as though no one is watching you; Love as though you have never been hurt before; Sing as though no one can hear you; Live as though heaven is on earth." — Souza