Extracting Argument and Domain Words for Identifying Argument Components in Texts
Huy V. Nguyen, Diane J. Litman · 2015
Argument mining studies in natural language text often use lexical (e.g.n-grams) and syntactic (e.g.grammatical production rules) features with all possible values.In prior work on a corpus of academic essays, we demonstrated that such large and sparse feature spaces can cause difficulty for feature selection and proposed a method to design a more compact feature space.The proposed feature design is based on post-processing a topic model to extract argument and domain words.In this paper we investigate the generality of this approach, by applying our methodology to a new corpus of persuasive essays.Our experiments show that replacing n-grams and syntactic rules with features and constraints using extracted argument and domain words significantly improves argument mining performance for persuasive essays.