文章基本信息

标题：A Comparative Study to Understanding about Poetics Based on Natural Language Processing
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作者：Lingyi Zhang ; Junhui Gao
期刊名称：Open Journal of Modern Linguistics
印刷版ISSN：2164-2818
电子版ISSN：2164-2834
出版年度：2017
卷号：07
期号：05
页码：229-237
DOI：10.4236/ojml.2017.75017
语种：English
出版社：Scientific Research Publishing
摘要：This paper tries to find out five poets’ (Thomas Hardy, Wilde, Browning, Yeats, and Tagore) differences and similarities through analyzing their works on nineteenth Century by using natural language understanding technology and word vector model. Firstly, we collect enough poems from these five poets, build five corpus respectively, and calculate their high-frequency words, by using Natural Language Processing method. Then, based on the word vector model, we calculate the word vectors of the five poets’ high-frequency words, and combine the word vectors of each poet into one vector. Finally, we analyze the similarity between the combined word vectors by using the hierarchical clustering method. The result shows that the poems of Hardy, Browning, and Wilde are similar; the poems of Tagore and Yeats are relatively close—but the gap between the two is relatively large. In addition, we evaluate the stability of our approach by altering the word vector dimension, and try to analyze the results of clustering in a literary (poetic) perspective. Yeats and Tagore possessed a kind of mysticism poetics thought, while Hardy, Browning, and Wilde have the elements of realism combined with tragedy and comedy. The results are similar comparing to those we get from the word vector model.
关键词：Poets;Natural Language Processing;Word Vector Model;Similarity;Cluster Analysis