wiki-metrix

Notebook to compare wiki articles based on weltliteratur/fontane.

https://github.com/temporal-communities/wiki-metrix

Science Score: 67.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • 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
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (5.5%) to scientific vocabulary
Last synced: 7 months ago · JSON representation ·

Repository

Notebook to compare wiki articles based on weltliteratur/fontane.

Basic Info
  • Host: GitHub
  • Owner: temporal-communities
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
  • Homepage:
  • Size: 125 KB
Statistics
  • Stars: 4
  • Watchers: 3
  • Forks: 1
  • Open Issues: 0
  • Releases: 0
Created over 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme License Citation

README.md

WikiMetrix

DOI Open In Colab

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

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

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Dependencies

requirements.txt pypi
  • 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