{"id":32175169,"url":"https://github.com/uwnetlab/metaknowledge","last_synced_at":"2026-03-07T22:31:39.782Z","repository":{"id":35049570,"uuid":"39178389","full_name":"UWNETLAB/metaknowledge","owner":"UWNETLAB","description":"A Python library for doing bibliometric and network analysis in science and health policy research","archived":false,"fork":false,"pushed_at":"2022-06-09T10:16:55.000Z","size":26648,"stargazers_count":177,"open_issues_count":10,"forks_count":35,"subscribers_count":14,"default_branch":"master","last_synced_at":"2026-01-22T03:57:46.944Z","etag":null,"topics":["bibliometrics","citations","co-citation","informetrics","metaknowledge","natural-language-processing","scientometrics","social-network-analysis","sociology-of-science"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":"cake-contrib/Cake.Unity","license":"gpl-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/UWNETLAB.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2015-07-16T05:36:07.000Z","updated_at":"2025-12-19T05:21:15.000Z","dependencies_parsed_at":"2022-08-03T23:45:23.522Z","dependency_job_id":null,"html_url":"https://github.com/UWNETLAB/metaknowledge","commit_stats":null,"previous_names":["networks-lab/metaknowledge"],"tags_count":42,"template":false,"template_full_name":null,"purl":"pkg:github/UWNETLAB/metaknowledge","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UWNETLAB%2Fmetaknowledge","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UWNETLAB%2Fmetaknowledge/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UWNETLAB%2Fmetaknowledge/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UWNETLAB%2Fmetaknowledge/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/UWNETLAB","download_url":"https://codeload.github.com/UWNETLAB/metaknowledge/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UWNETLAB%2Fmetaknowledge/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29596329,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-18T20:59:56.587Z","status":"ssl_error","status_checked_at":"2026-02-18T20:58:41.434Z","response_time":162,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bibliometrics","citations","co-citation","informetrics","metaknowledge","natural-language-processing","scientometrics","social-network-analysis","sociology-of-science"],"created_at":"2025-10-21T19:26:28.837Z","updated_at":"2026-02-18T22:02:14.888Z","avatar_url":"https://github.com/UWNETLAB.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ca href=\"https://uwaterloo.ca/networks-lab/\"\u003e\u003cimg src=\"http://www.johnmclevey.com/assets/img/logo.png\" width=\"125\"  align=\"right\" /\u003e\u003c/a\u003e\n\n# metaknowledge\n\n`metaknowledge` is a Python3 package that simplifies bibliometric research using data from various sources. It reads a directory of plain text files containing meta-data on publications and citations, and writes to a variety of data structures that are suitable for quantitative, network, and text analyses. It handles large datasets (e.g. several million records) efficiently. You can find the [documentation](https://metaknowledge.readthedocs.io/).\n\n## Installing\n\nTo install run `python3 setup.py install`\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuwnetlab%2Fmetaknowledge","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fuwnetlab%2Fmetaknowledge","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuwnetlab%2Fmetaknowledge/lists"}