2007 Seventh IEEE International Conference on Data Mining
Extracting Product Comparisons from Discussion Boards
Omaha, Nebraska, USA
October 28-October 31
ISBN: 0-7695-3018-4
In recent years, product discussion forums have become a rich environment in which consumers and potential adopters exchange views and information. Researchers and practitioners are starting to extract user sentiment about products from user product reviews. Users often compare different products, stating which they like better and why. Extracting information about product comparisons offers a number of challenges; recognizing and normalizing entities (products) in the informal language of blogs and discussion groups require different techniques than those used for entity extraction in the more formal text of newspapers and scientific articles. We present a case study in extracting information about comparisons between running shoes and between cars, describe an effective methodology, and show how it produces insight into how consumers view the running shoe and car markets.
Citation:
Ronen Feldman, Moshe Fresco, Jacob Goldenberg, Oded Netzer, Lyle Ungar, "Extracting Product Comparisons from Discussion Boards," icdm, pp.469-474, 2007 Seventh IEEE International Conference on Data Mining, 2007