Vivian Lee Lay Shan, Gan Keng Hoon*, Tan Tien Ping, Rosni Abdullah
CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4801-4818, 2023, DOI:10.32604/cmc.2023.033752
Abstract Sentiment classification is a useful tool to classify reviews about sentiments and attitudes towards a product or service. Existing studies heavily rely on sentiment classification methods that require fully annotated inputs. However, there is limited labelled text available, making the acquirement process of the fully annotated input costly and labour-intensive. Lately, semi-supervised methods emerge as they require only partially labelled input but perform comparably to supervised methods. Nevertheless, some works reported that the performance of the semi-supervised model degraded after adding unlabelled instances into training. Literature also shows that not all unlabelled instances are equally useful; thus identifying the informative… More >
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