Novel2Vec: Characterising 19th Century Fiction via Word Embeddings

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Title: Novel2Vec: Characterising 19th Century Fiction via Word Embeddings
Authors: Grayson, Siobhán
Mulvany, Maria
Wade, Karen
Meaney, Gerardine
Greene, Derek
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Date: 21-Sep-2016
Abstract: Recently, considerable attention has been paid to word embedding algorithms inspired by neural network models. Given a large textual corpus, these algorithms attempt to derive a set of vectors which represent the corpus vocabulary in a new embedded space. This representation can provide a useful means of measuring the underlying similarity between words. Here we investigate this property in the context of annotated texts of 19th-century fiction by the authors Jane Austen, Charles Dickens, and Arthur Conan Doyle. We demonstrate that building word embeddings on these texts can provide us with an insight into how characters group differently under different conditions, allowing us to make comparisons across different novels and authors. These results suggest that word embeddings can potentially provide a useful tool in supporting quantitative literary analysis.
Funding Details: Irish Research Council
Science Foundation Ireland
Type of material: Conference Publication
Keywords: Machine learningStatistics
Language: en
Status of Item: Peer reviewed
Conference Details: 24th Irish Conference on Artificial Intelligence and Cognitive Science (AICS'16), University College Dublin, Dublin, Ireland, 20-21 September 2016
Appears in Collections:English, Drama & Film Research Collection
Computer Science Research Collection
UCD Humanities Institute Research Collection
Insight Research Collection

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