| | |
Summary: Appraisal Extraction for News Opinion Analysis at NTCIR-6
Kenneth Bloom Sterling Stein Shlomo Argamon
Department of Computer Science
Illinois Institute of Technology
10 W 31st St. Chicago, IL 60616
kbloom1@iit.edu stein@ir.iit.edu argamon@iit.edu
Abstract
We describe a system which uses lexical shallow
parsing to find adjectival "appraisal groups" in sen-
tences, which convey a positive or negative appraisal
of an item. We used a simple heuristic to detect opin-
ion holders, determining whether a person was being
quoted in a specific sentence or not, and if so, who. We
also explored the the use of unsupervised learners and
voting to increase our coverage.
Keywords: Appraisal theory, opinion extraction.
1 Introduction
Our entry to the NTCIR opinion track is based on
our appraisal extraction system which applies the at-
titude system from Martin and White's [4] Appraisal
|
