Automatic identification of pro and con reasons in online reviews
Published 1 January 2006Open access
Soo-Min Kim, Eduard Hovy
Citations225
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TL;DR
A maximum entropy model is trained on the resulting labeled set to subsequently extract pros and cons from online review sites that do not explicitly provide them, and the resulting system identifies pros andcons with 66% precision and 76% recall.
Abstract
In this paper, we present a system that automatically extracts the pros and cons from online reviews. Although many approaches have been developed for extracting opinions from text, our focus here is on extracting the reasons of the opinions, which may themselves be in the form of either fact or opinion. Leveraging online review sites with author-generated pros and cons, we propose a system for aligning the pros and cons to their sentences in review texts. A maximum entropy model is then trained on the resulting labeled set to subsequently extract pros and cons from online review sites that do not explicitly provide them. Our experimental results show that our resulting system identifies pros and cons with 66% precision and 76% recall.
Keywords
Computer Science
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