NRC-Canada-2014: Detecting Aspects and Sentiment in Customer Reviews
Published 1 January 2014Open access
Svetlana Kiritchenko, Xiaodan Zhu, Colin Cherry, Saif M. Mohammad
Citations709
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TL;DR
Submissions to SemEval-2014 stood first in detecting aspect categories, first in detects sentiment towards aspects categories, third in detecting aspects terms, and first and second in detecting sentiment towards aspect terms in the laptop and restaurant domains, respectively.
Abstract
Reviews depict sentiments of customers towards various aspects of a product or service. Some of these aspects can be grouped into coarser aspect categories. SemEval-2014 had a shared task (Task 4) on aspect-level sentiment analysis, with over 30 teams participated. In this pa-per, we describe our submissions, which stood first in detecting aspect categories, first in detecting sentiment towards aspect categories, third in detecting aspect terms, and first and second in detecting senti-ment towards aspect terms in the laptop and restaurant domains, respectively. 1
Keywords
Computer Science
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