Paper: Mining Opinion Words and Opinion Targets in a Two-Stage Framework

ACL ID P13-1173
Title Mining Opinion Words and Opinion Targets in a Two-Stage Framework
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013
Authors

This paper proposes a novel two-stage method for mining opinion words and opinion targets. In the first stage, we propose a Sentiment Graph Walking algo- rithm, which naturally incorporates syn- tactic patterns in a Sentiment Graph to ex- tract opinion word/target candidates. Then random walking is employed to estimate confidence of candidates, which improves extraction accuracy by considering confi- dence of patterns. In the second stage, we adopt a self-learning strategy to refine the results from the first stage, especially for filtering out high-frequency noise terms and capturing the long-tail terms, which are not investigated by previous meth- ods. The experimental results on three real world datasets demonstrate the effective- ness of our approach compared with state- of-the-art uns...