Change Details

Create a medawiki-utilities bot to find articles in given categories, category trees, and lists. For each such article, find passages with (1) facts and statistics which are likely to have become out of date and have not been updated in a given number of years, and optionally (2) phrases which are likely unclear. Add an indication of the location and the text of those passages either to the page in question using templates, to a bookkeeping page with other page names as headings, and/or to a database local to the bot. Use a customizable array of keywords and regular expressions and measures of text comprehensibility (or optionally, the DELPH-IN LOGIN parser [ http://erg.delph-in.net/logon ]) to find such passages for review. Use an algorithm at least as good as that in T89763#1066043 to pre-compute the age of each word in an article (to avoid the move and blanking issues described in e.g., http://wikitrust.soe.ucsc.edu/talks-and-papers ) before processing each article of interest. Present flagged passages to one or more subscribed reviewers. Update the source template, if any, with the reviewer(s)' response, but keep the original text as part of the template. When reviewers disagree, update the template, if any, to reflect that fact, and present the question to a third reviewer to break the tie. Wiki page: https://www.mediawiki.org/wiki/Accuracy_review Primary mentor: @jsalsman Co-mentors: Maribel Acosta and Fabian Flöck Skills: Python 3, natural language processing Estimated project time for a senior contributor: 2 weeks Microtasks: Document updated schema. Improve candidate passage queue management, reviewer workflow, reviewer reputation database, and reporting. Include double-blinded identity and action codings for reviewer reputation database.

Create a medawiki-utilities bot to find articles in given categories, category trees, and lists. For each such article, find passages with (1) facts and statistics which are likely to have become out of date and have not been updated in a given number of years, and optionally (2) phrases which are likely unclear. Add an indication of the location and the text of those passages either to the page in question using templates, to a bookkeeping page with other page names as headings, and/or to a database local to the bot. Use a customizable array of keywords and regular expressions and measures of text comprehensibility (or optionally, the DELPH-IN LOGIN parser [ http://erg.delph-in.net/logon ]) to find such passages for review. Use an algorithm at least as good as that in T89763#1066043 to pre-compute the age of each word in an article (to avoid the move and blanking issues described in e.g., http://wikitrust.soe.ucsc.edu/talks-and-papers ) before processing each article of interest. Present flagged passages to one or more subscribed reviewers. Update the source template, if any, with the reviewer(s)' response, but keep the original text as part of the template. When reviewers disagree, update the template, if any, to reflect that fact, and present the question to a third reviewer to break the tie. Wiki page: https://www.mediawiki.org/wiki/Accuracy_review Primary mentor: @jsalsman Co-mentors: @Maribelacosta and Fabian Flöck Skills: Python 3, natural language processing Estimated project time for a senior contributor: 2 weeks Microtasks: Document updated schema. Improve candidate passage queue management, reviewer workflow, reviewer reputation database, and reporting. Include double-blinded identity and action codings for reviewer reputation database.

Create a medawiki-utilities bot to find articles in given categories, category trees, and lists. For each such article, find passages with (1) facts and statistics which are likely to have become out of date and have not been updated in a given number of years, and optionally (2) phrases which are likely unclear. Add an indication of the location and the text of those passages either to the page in question using templates, to a bookkeeping page with other page names as headings, and/or to a database local to the bot. Use a customizable array of keywords and regular expressions and measures of text comprehensibility (or optionally, the DELPH-IN LOGIN parser [ http://erg.delph-in.net/logon ]) to find such passages for review. Use an algorithm at least as good as that in T89763#1066043 to pre-compute the age of each word in an article (to avoid the move and blanking issues described in e.g., http://wikitrust.soe.ucsc.edu/talks-and-papers ) before processing each article of interest. Present flagged passages to one or more subscribed reviewers. Update the source template, if any, with the reviewer(s)' response, but keep the original text as part of the template. When reviewers disagree, update the template, if any, to reflect that fact, and present the question to a third reviewer to break the tie. Wiki page: https://www.mediawiki.org/wiki/Accuracy_review Primary mentor: @jsalsman Co-mentors: @Maribel Aacosta and Fabian Flöck Skills: Python 3, natural language processing Estimated project time for a senior contributor: 2 weeks Microtasks: Document updated schema. Improve candidate passage queue management, reviewer workflow, reviewer reputation database, and reporting. Include double-blinded identity and action codings for reviewer reputation database.