Edit 2019/Machine learning for wiki by university students: Submissions:2019/“Wikipedians are born, not made” – applying the learnings from a 10-year-old research paper after all

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This submission has been designated as a lightning talk at WikiConference North America 2019.



Title:

“Wikipedians are born, not made” – applying the learnings from a 10-year-old research paper after all

Theme:

Reliability of Information

Type of session:

Presentation

Abstract:

slides

In the recent past, artificial intelligence and machine learning were tools for specialists and computer scientists. Now, recent advances in technology, data availability, and social awareness have greatly increased the ease with which students can use techniques in data science to do interesting research in Wikimedia projects as part of a routine college learning experience.

This presentation will present Wikimedia-based machine learning projects at the University of Virginia's School of Data Science as examples of projects which any students might do to practice their lessons and be awesome in the wiki.

  • automated detection of misconduct
  • suggesting academic papers as sources for wiki articles
  • computer vision to sort images in Wikimedia Commons
  • fair representation of underrepresented groups in academia

Academic Peer Review option:

No

Author name:

Lane Rasberry

E-mail address:

lane@bluerasberry.com

Wikimedia username:

bluerasberry

Affiliated organization(s):

School of Data Science at the University of Virginia

Estimated time:

15 minutes

Preferred room size:

any

Special requests:

Have you presented on this topic previously? If yes, where/when?:

no

If your submission is not accepted, would you be open to presenting your topic in another part of the program? (e.g. lightning talk or unconference session)

yes, lightning talk




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