Chicago Machine Learning Meetup

Bing Liu will be presenting on Sentiment Analysis: Abstraction and Techniques
Sentiment analysis or opinion mining is the computational study of people's opinions, appraisals, and emotions toward entities, events and their attributes. Opinions are important because they are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are to a considerable degree conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. In the past 10 years, sentiment analysis attracted a great deal of attentions from both academia and industry due to many challenging research problems and a wide range of applications. In this talk, I will first discuss an abstraction of the problem to provide a structure to the unstructured text. I will then introduce some current techniques to deal with some of the sub-problems, which all present major challenges for NLP, text mining, and machine learning.

Biography: Bing Liu is a professor of Computer Science at University of Illinois at Chicago (UIC). His research interests include
opinion mining and sentiment analysis, Web mining, and data mining. He is the author of the widely used textbook "Web Data Mining: Exploring Hyperlinks, Contents and Usage Data". His research on detecting opinion spam (fake reviews) was recently featured in a front page article of The New York Times.