Analyzing online discussion for marketing intelligence

We present a system that gathers and analyzes online discussion as it relates to consumer products. Weblogs and online message boards provide forums that record the voice of the public. Woven into this discussion is a wide range of opinion and commentary about consumer products. Given its volume, format and content, the appropriate approach to understanding this data is large-scale web and text data mining. By using a wide variety of state-of-the-art techniques including crawling, wrapping, text classification and computational linguistics, online discussion is gathered and annotated within a framework that provides for interactive analysis that yields marketing intelligence for our customers. Categories and Subject Descriptors: H.3.3: Information Search and Retrieval General Terms: Algorithms, Experimentation

• Type: Conference
• Year: 2005
• Where: WWW
• Authors: Natalie S. Glance, Matthew Hurst, Kamal Nigam, Matthew Siegler, Robert Stockton, Takashi Tomokiyo
• Keywords: Consumer Products, Internet Technology, Online Discussion, Text Data Mining, WWW 2005