Sentiment Classification using N-gram IDF and Automated Machine Learning [article]

Rungroj Maipradit, Hideaki Hata, Kenichi Matsumoto
2019 arXiv   pre-print
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.
arXiv:1904.12162v2 fatcat:cp7javhekjdvtkwynpd53js5ru