1. A method, comprising: matching, by a processor, a trained classifier associated with a first domain to a target classifier associated with a second domain, the matching being based at least in part on identifying a common attribute between the trained classifier and the target classifier; selecting an identifier from the trained classifier, the identifier being a predictor of a sentiment of textual data; and associating the identifier with the target classifier, the target classifier being configured to categorize the textual data within the second domain using the identifier.
1. A method, comprising: matching, by a processor, a trained classifier associated with a first domain to a target classifier associated with a second domain, the matching being based at least in part on identifying a common attribute between the trained classifier and the target classifier; selecting an identifier from the trained classifier, the identifier being a predictor of a sentiment of textual data; and associating the identifier with the target classifier, the target classifier being configured to categorize the textual data within the second domain using the identifier. 2. The method of claim 1 , wherein the textual data is opinion data that is posted on the Internet.