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Sentiment Classification using N-gram IDF and Automated Machine Learning
April 27, 2019 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Rungroj Maipradit, Hideaki Hata, Kenichi Matsumoto
arXiv ID
1904.12162
Category
cs.IR: Information Retrieval
Cross-listed
cs.CL
Citations
13
Venue
arXiv.org
Last Checked
4 months ago
Abstract
We propose a sentiment classification method with a general machine learning framework. For feature representation, n-gram IDF is used to extract software-engineering-related, dataset-specific, positive, neutral, and negative n-gram expressions. For classifiers, an automated machine learning tool is used. In the comparison using publicly available datasets, our method achieved the highest F1 values in positive and negative sentences on all datasets.
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