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A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics

The use of Project Gutenberg (PG) as a text corpus has been extremely popular in statistical analysis of language for more than 25 years. However, in contrast to other major linguistic datasets of similar importance, no consensual full version of PG exists to date. In fact, most PG studies so far ei...

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Autores principales: Gerlach, Martin, Font-Clos, Francesc
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516435/
https://www.ncbi.nlm.nih.gov/pubmed/33285901
http://dx.doi.org/10.3390/e22010126
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author Gerlach, Martin
Font-Clos, Francesc
author_facet Gerlach, Martin
Font-Clos, Francesc
author_sort Gerlach, Martin
collection PubMed
description The use of Project Gutenberg (PG) as a text corpus has been extremely popular in statistical analysis of language for more than 25 years. However, in contrast to other major linguistic datasets of similar importance, no consensual full version of PG exists to date. In fact, most PG studies so far either consider only a small number of manually selected books, leading to potential biased subsets, or employ vastly different pre-processing strategies (often specified in insufficient details), raising concerns regarding the reproducibility of published results. In order to address these shortcomings, here we present the Standardized Project Gutenberg Corpus (SPGC), an open science approach to a curated version of the complete PG data containing more than 50,000 books and more than [Formula: see text] word-tokens. Using different sources of annotated metadata, we not only provide a broad characterization of the content of PG, but also show different examples highlighting the potential of SPGC for investigating language variability across time, subjects, and authors. We publish our methodology in detail, the code to download and process the data, as well as the obtained corpus itself on three different levels of granularity (raw text, timeseries of word tokens, and counts of words). In this way, we provide a reproducible, pre-processed, full-size version of Project Gutenberg as a new scientific resource for corpus linguistics, natural language processing, and information retrieval.
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spelling pubmed-75164352020-11-09 A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics Gerlach, Martin Font-Clos, Francesc Entropy (Basel) Article The use of Project Gutenberg (PG) as a text corpus has been extremely popular in statistical analysis of language for more than 25 years. However, in contrast to other major linguistic datasets of similar importance, no consensual full version of PG exists to date. In fact, most PG studies so far either consider only a small number of manually selected books, leading to potential biased subsets, or employ vastly different pre-processing strategies (often specified in insufficient details), raising concerns regarding the reproducibility of published results. In order to address these shortcomings, here we present the Standardized Project Gutenberg Corpus (SPGC), an open science approach to a curated version of the complete PG data containing more than 50,000 books and more than [Formula: see text] word-tokens. Using different sources of annotated metadata, we not only provide a broad characterization of the content of PG, but also show different examples highlighting the potential of SPGC for investigating language variability across time, subjects, and authors. We publish our methodology in detail, the code to download and process the data, as well as the obtained corpus itself on three different levels of granularity (raw text, timeseries of word tokens, and counts of words). In this way, we provide a reproducible, pre-processed, full-size version of Project Gutenberg as a new scientific resource for corpus linguistics, natural language processing, and information retrieval. MDPI 2020-01-20 /pmc/articles/PMC7516435/ /pubmed/33285901 http://dx.doi.org/10.3390/e22010126 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gerlach, Martin
Font-Clos, Francesc
A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics
title A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics
title_full A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics
title_fullStr A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics
title_full_unstemmed A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics
title_short A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics
title_sort standardized project gutenberg corpus for statistical analysis of natural language and quantitative linguistics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516435/
https://www.ncbi.nlm.nih.gov/pubmed/33285901
http://dx.doi.org/10.3390/e22010126
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