Moderator Tools/Automoderator/Testing/ja

チームは、機械学習モデルに基づいて悪質な編集を自動的にリバート「」というツールを開発中です. - ClueBot NGやSeroBOT、Dexbotなどのコミュニティの反荒らしボットと同じような機能を果たします. コミュニティがAutomoderatorの精度をテスト・評価できるように、過去の編集とAutomoderatorがそれをリバートしたかどうかのデータを含むテスト用スプレッドシートを用意しています.

オートモデレーターの決定は、機械学習モデルによる採点と内部設定の組み合わせによって決まります. モデルは再トレーニングにより時間とともに改善されますが、追加で内部ルールを定義することで、その精度を高めることを検討しています. たとえば、Automoderatorは、利用者が自分の編集内容をリバートする行為を荒らしと誤認することしばしば観測されます. こういった問題を改善するために、このボットの癖を探しています. 同様の例の特定にご協力をお願いいたします.

このテストは必ずしもAutomoderatorの最終形式を反映しているわけではないことに注意してください. あくまでこのテストの結果を使用してテストを改善します.



Automoderatorのテスト方法



 * If you have a Google account:
 * Use the Google Sheet link below and make a copy of it
 * You can do this by clicking File > Make a Copy ... after opening the link.
 * After your copy has loaded, click Share in the top corner, then give any access to avardhana@undefinedwikimedia.org (leaving 'Notify' checked), so that we can aggregate your responses to collect data on Automoderator's accuracy.
 * Alternatively, you can change 'General access' to 'Anyone with the link' and share a link with us directly or on-wiki.
 * Alternatively, use the .ods file link to download the file to your computer.
 * After adding your decisions, please send the sheet back to us at avardhana@undefinedwikimedia.org, so that we can aggregate your responses to collect data on Automoderator's accuracy.

After accessing the spreadsheet...


 * 1) Follow the instructions in the sheet to select a random dataset, review 30 edits, and then uncover what decisions Automoderator would make for each edit.
 * 2) Feel free to explore the full data in the 'Edit data & scores' tab.
 * 3) If you want to review another dataset please make a new copy of the sheet to avoid conflicting data.
 * 4) Join the discussion on the talk page.

'' Alternatively, you can simply dive in to the 'Edit data & scores' tab and start investigating the data directly. ''

''* We welcome translations of this sheet - if you would like to submit a translation please translate a copy and send it back to us at swalton@undefinedwikimedia.org. ''

If you want a sheet generated with data from another Wikipedia please let us know and we can create one.



Automoderatorについて
Automoderator’s model is trained exclusively on Wikipedia’s main namespace pages, limiting its dataset to edits made to Wikipedia articles. Further details can be found below:



内部コンフィグレーション
In the current version of the spreadsheet, in addition to considering the model score, Automoderator does not take actions on:


 * Edits made by administrators
 * Edits made by bots
 * Edits which are self-reverts
 * New page creations

The datasets contain edits which meet these criteria, but Automoderator should never say it will revert them. This behaviour and the list above will be updated as testing progresses if we add new exclusions or configurations.



注意レベル
In this test Automoderator has five 'caution' levels, defining the revert likelihood threshold above which Automoderator will revert an edit.


 * At high caution, Automoderator will need to be very confident to revert an edit. This means it will revert fewer edits overall, but do so with a higher accuracy.


 * At low caution, Automoderator will be less strict about its confidence level. It will revert more edits, but be less accurate.

The caution levels in this test have been set by the Moderator Tools team based on our observations of the models accuracy and coverage. To illustrate the number of reverts expected at different caution levels see below:

'' If you would like us to pull this data for another Wikimedia project just let us know on the talk page. ''

Score an individual edit
We have created a simple user script to retrieve a Revert Risk score for an individual edit. Simply import User:JSherman (WMF)/revertrisk.js into your commons.js with  on English Wikipedia, or   on other wikis.

You should then find a 'Get revert risk score' in the Tools menu in your sidebar. Note that this will only display the model score, and does not take into account Automoderator's internal configurations as detailed above. See the table above for the scores above which we are investigating Automoderator's false positive rate.