… for sentiment classification, active learning for imbalanced sentiment classification faces …
As a specific type of sentiment classification, imbalanced sentiment classification deals with the …

… to the performance of sentiment classification algorithms when facing imbalanced data, we
introduce a novel over-sampling method to address data imbalance. Unlike conventional over…

… In this subsection, we report the performances of supervised methods for imbalanced
sentiment classification (The unlabeled data is not involved). For thorough comparison, various …

… strategy in handling the imbalanced problems in real sentiment classification applications. …
We call this specific kind of sentiment classification as imbalanced sentiment classification, …

… imbalance of review texts on the positive–negative classes. In this paper, we pay attention to
the sentiment classification problem of imbalanced … aimed to text sentiment classification we …

… problem of unbalanced data sets in supervised sentiment classification in a multi-lingual
context. … shows a slight sensitivity to imbalance in comparison with Support Vector Machines. …

… for Twitter sentiment classification from multi-class imbalanced data described by a sparse
and high-dimensional feature space. The proposed classification framework consisted of five …

… In contrast to those approaches that discuss imbalanced sentiment classification, we … with
imbalanced data, like sampling techniques (Van Hulse, Khoshgoftaar, & Napolitano, 2007). …

… to tweet sentiment classification performance when training from class imbalanced data. The
… Section II describes previous research on tweet sentiment and how class imbalance has …

… classification compared with binary sentiment classification. … imbalanced sentiment and
emotion classification. Our approach improves imbalanced sentiment and emotion classification …