ArticleEntropy (Basel, Switzerland)2020
A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics.
Article in Entropy (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
15 citing papers in PubMed.
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- The dynamics of higher-order novelties.Nature communications · 2025Article
- Narrative reversals and story success.Science advances · 2024Article
- The rising entropy of English in the attention economy.Communications psychology · 2024Article
- PHONEME-LEVEL BERT FOR ENHANCED PROSODY OF TEXT-TO-SPEECH WITH GRAPHEME PREDICTIONS.Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) · 2023Article
- The 3d Mind Model characterizes how people understand mental states across modern and historical cultures.Affective science · 2022Article
- Approximate Entropy in Canonical and Non-Canonical Fiction.Entropy (Basel, Switzerland) · 2022Article
- Storywrangler: A massive exploratorium for sociolinguistic, cultural, socioeconomic, and political timelines using Twitter.Science advances · 2021Article
- Article
- A Note on the Reproducibility of Chaos Simulation.Entropy (Basel, Switzerland) · 2020Article
- Information Theory and Language.Entropy (Basel, Switzerland) · 2020Article
- The Brevity Law as a Scaling Law, and a Possible Origin of Zipf's Law for Word Frequencies.Entropy (Basel, Switzerland) · 2020Article
- From Boltzmann to Zipf through Shannon and Jaynes.Entropy (Basel, Switzerland) · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 3 × 10 9 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.