Self-training Strategies for Sentiment Analysis: An Empirical Study

Sentiment analysis is a crucial task in natural language processing that involves identifying and extracting subjective sentiment from text. Self-training has recently emerged as an economical and efficient technique for developing sentiment analysis models by leveraging a small amount of labeled data and a large amount of unlabeled data. However, given a set of training data, how to utilize them to conduct self-training makes a significant difference in the final performance of the model. We refer to this methodology as …

analysis cs.cl data language language processing natural natural language natural language processing processing self-training sentiment sentiment analysis small strategies study text training