TA6 - Opinion Mining and Summarization on the Web
Time: Monday, April 21 (half-day, morning, 8:30am to 12:00noon)
Location: Room 305B (Level 3)
Opinion mining, also known as sentiment analysis, became an important research area in recent years due to many interesting research problems and practical applications. To suit the WWW audience, I will focus on opinion mining from the user-generated content on the Web, e.g., customer reviews, forum posts and blogs. It is now well recognized that the user-generated content contains valuable information that can be exploited for many applications. Let us use customer reviews as an example. A consumer or a potential buyer of a product always wants to know the opinions of existing users of the product before deciding to purchase it. A product manufacturer also wants to find consumer opinions about its products and those of its competitors. Such information can be used for marketing and product improvements. However, for many products, the number of reviews can be large. Some popular products get hundreds of reviews or more at some merchant sites. It is thus highly desirable to mine such opinions and produce a summary of the opinions. The same can also be said about forum posts and blogs. In this tutorial, I will introduce four main topics of opinion mining, i.e., sentiment classification, feature-based opinion mining and summarization, mining comparative and superlative sentences, and opinion spam. All parts of the tutorial will have a mix of research and industry flavor, addressing seminal research concepts and looking at the technology from an industry angle. Apart from researchers and gradate students, we particularly encourage practitioners from industry to participate because of many important applications.
Bing Liu, University of Illinois at Chicago (USA)
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