In the context of interdisciplinary research,using computer technology to further mine keywords in cultural texts and carry out semantic analysis can deepen the understanding of texts,and provide quantitative support ...In the context of interdisciplinary research,using computer technology to further mine keywords in cultural texts and carry out semantic analysis can deepen the understanding of texts,and provide quantitative support and evidence for humanistic studies.Based on the novel A Dream of Red Mansions,the automatic extraction and classification of those sentiment terms in it were realized,and detailed analysis of large-scale sentiment terms was carried out.Bidirectional encoder representation from transformers(BERT) pretraining and fine-tuning model was used to construct the sentiment classifier of A Dream of Red Mansions.Sentiment terms of A Dream of Red Mansions are divided into eight sentimental categories,and the relevant people in sentences are extracted according to specific rules.It also tries to visually display the sentimental interactions between Twelve Girls of Jinling and Jia Baoyu along with the development of the episode.The overall F_(1) score of BERT-based sentiment classifier reached 84.89%.The best single sentiment score reached 91.15%.Experimental results show that the classifier can satisfactorily classify the text of A Dream of Red Mansions,and the text classification and interactional analysis results can be mutually verified with the text interpretation of A dream of Red Mansions by literature experts.展开更多
基金supported by the Fundamental Research Funds for the Central Universities (2019XD-A03-3)the Beijing Key Lab of Network System and Network Culture (NSNC-202 A09)。
文摘In the context of interdisciplinary research,using computer technology to further mine keywords in cultural texts and carry out semantic analysis can deepen the understanding of texts,and provide quantitative support and evidence for humanistic studies.Based on the novel A Dream of Red Mansions,the automatic extraction and classification of those sentiment terms in it were realized,and detailed analysis of large-scale sentiment terms was carried out.Bidirectional encoder representation from transformers(BERT) pretraining and fine-tuning model was used to construct the sentiment classifier of A Dream of Red Mansions.Sentiment terms of A Dream of Red Mansions are divided into eight sentimental categories,and the relevant people in sentences are extracted according to specific rules.It also tries to visually display the sentimental interactions between Twelve Girls of Jinling and Jia Baoyu along with the development of the episode.The overall F_(1) score of BERT-based sentiment classifier reached 84.89%.The best single sentiment score reached 91.15%.Experimental results show that the classifier can satisfactorily classify the text of A Dream of Red Mansions,and the text classification and interactional analysis results can be mutually verified with the text interpretation of A dream of Red Mansions by literature experts.
