Automated learning of appraisal extraction patterns
K R Bloom, Shlomo Argamon · 2010
This paper describes a grammatically motivated system for extracting opinionated text. A technique for extracting appraisal expressions has been described in previous work, using manually constructed syntactic linkages to locate targets of the opinions. The system extracts attitudes using a general lexicon—and some candidate targets using a domain specific lexicon—and finds additional targets using the syntactic linkages. In this paper, we discuss a technique for automatically learning the syntactic linkages from a list of all extracted attitudes and the list of candidate targets. The accuracy of the new learned linkages is comparable to the accuracy of the old manual linkages.