The Gutenberg English Poetry Corpus: Exemplary Quantitative Narrative Analyses

A. Jacobs
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引用次数: 43

Abstract

This paper describes a corpus of about 3000 English literary texts with about 250 million words extracted from the Gutenberg project that span a range of genres from both fiction and non-fiction written by more than 130 authors (e.g., Darwin, Dickens, Shakespeare). Quantitative Narrative Analysis (QNA) is used to explore a cleaned subcorpus, the Gutenberg English Poetry Corpus (GEPC) which comprises over 100 poetic texts with around 2 million words from about 50 authors (e.g., Keats, Joyce, Wordsworth). Some exemplary QNA studies show author similarities based on latent semantic analysis, significant topics for each author or various text-analytic metrics for George Eliot’s poem ‘How Lisa Loved the King’ and James Joyce’s ’Chamber Music’, concerning e.g. lexical diversity or sentiment analysis. The GEPC is particularly suited for research in Digital Humanities, Natural Language Processing or Neurocognitive Poetics, e.g. as training and test corpus, or for stimulus development and control.
古腾堡英语诗歌语料库:典型的定量叙事分析
本文描述了一个从古腾堡计划中提取的约3000个英语文学文本的语料库,约2.5亿字,涵盖了130多位作者(如达尔文、狄更斯、莎士比亚)的小说和非小说等一系列体裁。定量叙事分析(QNA)用于探索一个经过清理的子语料库,即古腾堡英语诗歌语料库(GEPC),该语料库包含约50位作者(如济慈、乔伊斯、华兹华斯)的100多篇诗歌文本,约200万字。一些典型的QNA研究显示了基于潜在语义分析的作者相似性,每个作者的重要主题或乔治·艾略特的诗歌“丽莎如何爱国王”和詹姆斯·乔伊斯的“室内乐”的各种文本分析指标,例如词汇多样性或情感分析。GEPC特别适合于数字人文、自然语言处理或神经认知诗学的研究,例如作为训练和测试语料库,或用于刺激的开发和控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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