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.
Feldman, Ronen, Moshe Fresko, Jacob Goldenberg, Oded Netzer, and Lyle Ungar. "Extracting Product Comparisons from Discussion Boards." Proceedings of the 2007 IEEE International Conference on Data Mining 1 (October 2007): 469-474.
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