Genre Classification Workflow For the ESTC

This is a preprint of an upcoming article. Abstract below:This article introduces an open-box workflow for labelling 94 percent of the English Short Title Catalogue (ESTC) with a unified genre classification scheme, as well as an approach to evaluating the classifications. As the ESTC covers most of the surviving books published in the early modern Anglosphere, the categorisation offers new opportunities for large-scale quantitative research on early modern book trade. Our evaluation process directly engages with the ambiguity of any genre labelling or annotation schemes of Early Modern books and highlights problematic boundaries between the categories. We also provide summary statistics about the genre-wise composition of the ESTC, demonstrate how the new data can be used to detect biases in other data sets of early modern books and discuss further possibilities in genre-related computational work with the ESTC.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-14
DOI
https://doi.org/10.5281/zenodo.14166077
Primary Topic
Authorship Attribution and Profiling
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Genre Classification Workflow For the ESTC

Zenodo (CERN European Organization for Nuclear Research)
Authorship Attribution and Profiling
article

Genre Classification Workflow For the ESTC

article en

Abstract

This is a preprint of an upcoming article. Abstract below:This article introduces an open-box workflow for labelling 94 percent of the English Short Title Catalogue (ESTC) with a unified genre classification scheme, as well as an approach to evaluating the classifications. As the ESTC covers most of the surviving books published in the early modern Anglosphere, the categorisation offers new opportunities for large-scale quantitative research on early modern book trade. Our evaluation process directly engages with the ambiguity of any genre labelling or annotation schemes of Early Modern books and highlights problematic boundaries between the categories. We also provide summary statistics about the genre-wise composition of the ESTC, demonstrate how the new data can be used to detect biases in other data sets of early modern books and discuss further possibilities in genre-related computational work with the ESTC.

Zenodo (CERN European Organization for Nuclear Research)
University of Helsinki (FI)
Openalex Percentile: Top 65%
Authorship Attribution and Profiling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.