wiki-metrix
Notebook to compare wiki articles based on weltliteratur/fontane.
Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (5.5%) to scientific vocabulary
Repository
Notebook to compare wiki articles based on weltliteratur/fontane.
Basic Info
Statistics
- Stars: 4
- Watchers: 3
- Forks: 1
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
WikiMetrix
Jupyter notebook to retrieve and visualise article-level Wikipedia data
The collaboratively edited online encyclopaedia Wikipedia currently contains over 60 million articles in over 300 language editions, covering topics across many fields of knowledge. Scholars of reception-oriented literary studies have also discovered Wikipedia as a research topic and a data resource, as it collects encyclopaedic entries and metadata about literature, authors, literary works, genres, periods and other categories relevant to the history of literature.
Data-analytical evaluation of various Wikipedia metrics opens up an opportunity to empirically assess engagement with literature on Wikipedia and to further diversify statements about literary canonisation, valuation practices and popularity in the context of open encyclopaedia projects. This Jupyter notebook, developed by Research Area 5 Building Digital Communities of the Cluster of Excellence Temporal Communities, is a user-friendly tool for retrieving and visualising article-level data from Wikipedia.
Work based on weltliteratur/fontane.
Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy in the context of the Cluster of Excellence Temporal Communities: Doing Literature in a Global Perspective – EXC 2020 – Project ID 390608380.
Owner
- Name: EXC Temporal Communities
- Login: temporal-communities
- Kind: organization
- Website: https://temporal-communities.de/
- Repositories: 1
- Profile: https://github.com/temporal-communities
EXC 2020 Temporal Communities
Citation (CITATION.cff)
cff-version: 1.2.0
title: WikiMetrix
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- affiliation: "Freie Universität Berlin, Deutschland"
family-names: Illmer
given-names: Viktor J.
orcid: https://orcid.org/0000-0002-7334-781X
- affiliation: "Freie Universität Berlin, Deutschland"
family-names: Soethaert
given-names: Bart
orcid: https://orcid.org/0000-0002-3845-605X
- affiliation: "Freie Universität Berlin, Deutschland"
family-names: Welz
given-names: Lilly
- affiliation: "Freie Universität Berlin, Deutschland"
family-names: Fischer
given-names: Frank
orcid: https://orcid.org/0000-0003-2419-6629
- affiliation: "Humboldt-Universität zu Berlin, Deutschland"
family-names: "Jäschke"
given-names: Robert
orcid: https://orcid.org/0000-0003-3271-9653
repository-code: "https://github.com/temporal-communities/wiki-metrix"
abstract: >-
Jupyter notebook to retrieve and visualise article-level
Wikipedia data
license: MIT
preferred-citation:
type: "conference-paper"
title: "Literatur im Wikiversum – Eine praktische Annäherung über API-Abfragen und Wikipedia-Metriken"
abstract: "Die kollaborativ erstellte Online-Enzyklopädie Wikipedia bietet mit derzeit über 60 Millionen Artikeln in über 300 Sprachversionen Informationen zu den unterschiedlichsten Wissensbereichen. Auch die rezeptionsorientierte Literaturwissenschaft hat das Projekt inzwischen als Forschungsgegenstand und Datenressource entdeckt, da es viele enzyklopädische Beiträge und Metadaten zur Literatur und zum literarischen Leben versammelt, zu Autor*innen, literarischen Werken, Genres, Epochen und anderen literaturgeschichtlich relevanten Kategorien. Die datenanalytische Auswertung verschiedener Wikipedia-Metriken ermöglicht es, die Auseinandersetzung mit Literatur in Wikipedia evaluierbar zu machen und Aussagen über literarische Kanonizität, Wertungspraktiken und Popularität im Kontext offener Enzyklopä dieprojekte weiter zu diversifizieren. Im Zentrum des (hands-on) Workshops steht die Wikipedia-API, mit deren Funktionsweise die Teilnehmer*innen vertraut gemacht werden. Sukzessive werden Abfrageskripte in Form eines Jupyter Notebooks erarbeitet."
authors:
- affiliation: "Freie Universität Berlin, Deutschland"
family-names: Illmer
given-names: Viktor J.
orcid: https://orcid.org/0000-0002-7334-781X
- affiliation: "Freie Universität Berlin, Deutschland"
family-names: Soethaert
given-names: Bart
orcid: https://orcid.org/0000-0002-3845-605X
- affiliation: "Freie Universität Berlin, Deutschland"
family-names: Welz
given-names: Lilly
- affiliation: "Freie Universität Berlin, Deutschland"
family-names: Fischer
given-names: Frank
orcid: https://orcid.org/0000-0003-2419-6629
- affiliation: "Humboldt-Universität zu Berlin, Deutschland"
family-names: "Jäschke"
given-names: Robert
orcid: https://orcid.org/0000-0003-3271-9653
date-released: "2024-02-21"
conference:
name: "DHd 2024 Quo Vadis DH"
alias: DHd2024
doi: 10.5281/zenodo.10698426
keywords:
- DHd2024
- Paper
- Workshop
- Wikipedia
- Literatur
- API
- Python
- Crowdsourcing
- "Einführung"
- Lehre
- Werkzeuge
license:
- CC-BY-4.0
GitHub Events
Total
- Watch event: 2
Last Year
- Watch event: 2
Dependencies
- XlsxWriter ==3.1.6
- kaleido ==0.2.1
- plotly ==5.14.1
- plotly-express ==0.4.1
- polars ==0.19.7
- pywikibot ==8.1.2
- requests ==2.31.0
- tqdm ==4.65.0