Mining Web Text for Brand Associations

Robert Malouf, Bradley Davidson, Ashli Sherman

Weblogs and other web text are an incredibly rich knowledge base, and the marketing industry is beginning to recognize the value of web texts as a source of information about their customers. However, the nature of web texts make them unsuitable for analysis using standard market research methods. In this paper, we describe the use of exploratory data analysis techniques to extract the associations patients and their caregivers have for eight leading medications for a seizure disorder. We first collect a list of candidate keywords which occur with a brand name or a variant spelling, and then cluster the keywords to construct a set of brand associations. To compare individual brands we measure the association between each brand name and any term from each of the clusters. Finally, using dimensionality reduction techniques, we plot the brand names, their associations, and their relationships as a brand association map.


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