{
  "abstract": "Networks or graphs are widely used across the sciences to represent relationships of many kinds. The igraph (https://igraph.org) software library supports graph construction, analysis, and visualisation, combining fast and robust performance with a low entry barrier. igraph pairs a fast core written in C with beginner-friendly interfaces in Python, R, and Mathematica. After twenty years of development, igraph 1.0 has been released, enabling public access to a robust and stable network analysis with over a million monthly downloads. Thanks to its cross-language design, igraph delivers both speed and flexibility: it can handle billions of edges, supports interactive plotting, integrates with notebooks, facilitates conversions to and from other network libraries, includes a rich library of graph layout and community detection algorithms, and has a detailed documentation including non-English translations. Modern testing features such as continuous integration, address sanitizers, stricter typing, and memory-managed vectors have also increased robustness. Hundreds of bug reports have been fixed and a community forum has been opened to connect users and developers. Specific effort has been made to broaden use and community participation by women, non-binary people, and other demographic groups typically underrepresented in open source software.",
  "abstract_shown": true,
  "affiliations": [
    "cynkra GmbH., Zürich, Switzerland",
    "Posit Software, PBC, Boston, Massachusetts, United States of America",
    "Center for Systems Biology Dresden, Dresden, Germany",
    "Reykjavik University, Reykjavík, Iceland",
    "Sixdegrees Ltd, Budapest, Hungary",
    "jitjit, Amsterdam, Netherlands",
    "Centre for Science and Technology Studies, Leiden University, Leiden, Zuid-Holland, Netherlands",
    "Northeastern University, Boston, Massachusett, United States of America",
    "Evolution & Ecology Research Centre, UNSW Sydney, Sydney, NSW, Australia",
    "School of Clinical Medicine, UNSW Sydney, Sydney, NSW, Australia"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Michael Antonov"
    },
    {
      "affs": [
        1
      ],
      "name": "Gábor Csárdi",
      "orcid": "0000-0001-7098-9676"
    },
    {
      "affs": [
        2,
        3
      ],
      "name": "Szabolcs Horvát",
      "orcid": "0000-0002-3100-523X"
    },
    {
      "affs": [
        0
      ],
      "name": "Kirill Müller",
      "orcid": "0000-0002-1416-3412"
    },
    {
      "affs": [
        4
      ],
      "name": "Tamás Nepusz",
      "orcid": "0000-0002-1451-338X"
    },
    {
      "affs": [
        5
      ],
      "name": "Daniel Noom"
    },
    {
      "affs": [
        0
      ],
      "name": "Maëlle Salmon",
      "orcid": "0000-0002-2815-0399"
    },
    {
      "affs": [
        6
      ],
      "name": "Vincent Traag",
      "orcid": "0000-0003-3170-3879"
    },
    {
      "affs": [
        7
      ],
      "name": "Brooke Foucault Welles",
      "orcid": "0000-0002-4155-8815"
    },
    {
      "affs": [
        8,
        9
      ],
      "name": "Fabio Zanini",
      "orcid": "0000-0001-7097-8539"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9kxm4taerzf9k.bib",
  "cited_by": 120,
  "doi": "10.1371/journal.pone.0355108",
  "fulltext_url": null,
  "id": "9kxm4taerzf9k",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0355108",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "3109|Complex Network Analysis Techniques"
    ]
  ],
  "openalex": "W4388843329",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0355108&type=printable",
  "pmcid": "PMC13436765",
  "pmid": "42550872",
  "published": "2026-08-04",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/9kxm4taerzf9k.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:18Z",
      "native_id": "W4388843329",
      "source": "openalex",
      "url": "https://doi.org/10.1371/journal.pone.0355108"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "openalex:3109|Complex Network Analysis Techniques",
      "subfield": "statistical-nonlinear"
    }
  ],
  "title": "igraph 1.0 enables fast and robust network analysis across programming languages",
  "title_text": "igraph 1.0 enables fast and robust network analysis across programming languages",
  "type": "peer-reviewed",
  "updated_at": "2026-11-09T13:21:01Z",
  "url": "https://research.draconitic.com/paper/9kxm4taerzf9k",
  "venue": "PLoS ONE",
  "versions": []
}