Reader-responses-to-translated-literature
Scripts for the DIOPTRA-L project (Digital Opinions on Translated Literature)
https://github.com/CentreForDigitalHumanities/Reader-responses-to-translated-literature
Science Score: 57.0%
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✓CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
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✓DOI references
Found 1 DOI reference(s) in README -
○Academic publication links
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○Scientific vocabulary similarity
Low similarity (7.2%) to scientific vocabulary
Keywords
Repository
Scripts for the DIOPTRA-L project (Digital Opinions on Translated Literature)
Basic Info
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Metadata Files
README.md
Reader responses to translated literature
This repository contains code for the DIOPTRA-L project by Haidee Kotze, Gys-Walt van Egdom, Corina Koolen and Utrecht University's Research Software Lab, and can be used to reproduce the publication
Kotze, Haidee & Janssen, Berit & Koolen, Corina & Plas, Luka & Egdom, Gys-Walt. (2021). Norms, affect and evaluation in the reception of literary translations in multilingual online reading communities: Deriving cognitive-evaluative templates from big data. Translation, Cognition & Behavior. 4. 10.1075/tcb.00060.kot.
Prerequisites
Python
Most of the scripts require Python 3.6. To install dependencies, run
pip install -r requirements.txt
R
The statistical analysis and visualization was performed in R, using the following libraries: - coin - dplyr - ggplot2 - Hmisc - irr - lme4 - reshape2 - rstatix
Steps to reproduce
- scrapers: Python scripts used to scrape reviews from Goodreads. Documentation on usage in that folder's README.
- preprocessing: Python scripts used to clean the data, and more specifically, tokenization.
- embeddings: Jupyter notebooks for training and evaluating word embeddings using word2vec. As the dataset is relatively small, the resulting embeddings were not informative for further research.
- analysis: Python scripts to collect and count translation lemmas, based on human annotations.
- collocations: Python scripts for finding collocations surrounding translation lemmas
- sentiment: Python scripts to count positive / negative and hedge terms in collocations.
- model: R scripts used to generate statistics and visualizations of the data.
Owner
- Name: Centre for Digital Humanities
- Login: CentreForDigitalHumanities
- Kind: organization
- Email: cdh@uu.nl
- Location: Netherlands
- Website: https://cdh.uu.nl/
- Repositories: 39
- Profile: https://github.com/CentreForDigitalHumanities
Interdisciplinary centre for research and education in computational and data-driven methods in the humanities.
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 1.2.0
title: Reader-responses-to-translated-literature
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- name: 'Research Software Lab, Centre for Digital Humanities, Utrecht University'
website: 'https://cdh.uu.nl/centre-for-digital-humanities/research-software-lab/'
city: Utrecht
country: NL
identifiers:
- type: doi
value: 10.5281/zenodo.10868077
repository-code: 'https://github.com/UUDigitalHumanitieslab/Reader-responses-to-translated-literature'
abstract: >-
This repository contains code for the DIOPTRA-L project by Haidee Kotze, Gys-Walt van Egdom, Corina Koolen and Utrecht University's Research Software Lab.
keywords:
- speech
- prosody
- classification
license: MIT
version: 0.0.1
date-released: '2024-03-25'
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