While there are a number of subjectivity lexicons available for research purposes, none can be used commercially. We describe the process of constructing subjectivity lexicon(s) for recognizing sentiment polarity in essays written by test-takers, to be used within a commercial essay-scoring system. We discuss ways of expanding a manually-built seed lexicon using dictionary-based, distributional in-domain and out-of-domain information, as well as using Amazon Mechanical Turk to help "clean up" the expansions. We show the feasibility of constructing a family of subjectivity lexicons from scratch using a combination of methods to attain competitive performance with state-of-art research-only lexicons. Furthermore, this is the first use, to our knowledge, of a paraphrase generation system for expanding a subjectivity lexicon. © 2012 Springer-Verlag.
CITATION STYLE
Beigman Klebanov, B., Burstein, J., Madnani, N., Faulkner, A., & Tetreault, J. (2012). Building subjectivity lexicon(s) from scratch for essay data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7181 LNCS, pp. 591–602). https://doi.org/10.1007/978-3-642-28604-9_48
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