Research:AFTRank

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Created
2012/12
Contact
Ryan Faulkner
Collaborators
Aaron Halfaker
Oliver Keyes
Dario Taraborelli
Duration:  2012-12 — 2013-
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This page is an incomplete draft of a research project.
Information is incomplete and is likely to change substantially before the project starts.


Key Personnel[edit]

  • Ryan Faulkner
  • Aaron Halfaker
  • Oliver Keyes
  • Dario Taraborelli

Project Summary[edit]

This project aims to develop and test a classifier to identify good feedback from a corpus of unmoderated/non-featured article feedback (v.5) posts. The design goals of AFTRank are the following:

  1. reduce the workload of feedback moderators by prefiltering feedback not worth being moderated:
    1. automatically hide or decrease the score of bad feedback without the need of hitting AbuseFilter
    2. increase the score of unmoderated good feedback
  2. correct the bias towards high-traffic articles produced by the current UI of the FeedbackPage:
    1. allow moderators to explore the large amount of feedback from low-traffic articles that hardly receives any attention
    2. surface feedback from articles with an expected higher feedback quality but low moderation activity

Methods[edit]

Dissemination[edit]

Wikimedia Policies, Ethics, and Human Subjects Protection[edit]

Benefits for the Wikimedia community[edit]

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