Research:Revision scoring as a service/Stories
This page documents stories written by people who found the project to be useful for them.
Updating WikiProject Medicine article assessments[edit]
Recent work in article quality assessment detection[1][2] can enable us to automatically identify which articles are most due to be re-assessed. Let's apply this method to WikiProject Medicine's stubs.
Discussion: Research:Screening WikiProject Medicine articles for quality
Andrew Lih experiments with ORES in the classroom[edit]
[...] having students excited and experiencing that instant dopamine hit when editing articles is a breath of fresh air when pleasurable interactions seem to be less frequent today than in Wikipedia’s early days.
Discussion: en:User:Fuzheado/ORES experiment
Smithsonian American Art Museum edit-a-thon[edit]
Our hand-assessed article ratings are looking quite stale. You may be skeptical of whether a machine learning algorithm can do a decent job of properly assessing articles. However, in just two weeks of experimenting with ORES, it seems to be far more preferable than putting stock in stub/start/C human-assessed ratings that may be months or years old. --Andrew Lih
Discussion: https://www.facebook.com/groups/glamwikius/permalink/579619518862783/ Results: en:Wikipedia:Meetup/DC/SAAM AU 2016#Harlem Renaissance artists
See also[edit]
- RA-UN, which uses Revscore to identify vandalism [1]
- WikiProject Cannabis (English Wikipedia)
References[edit]
- ↑ Warncke-Wang, M., Cosley, D., & Riedl, J. (2013, August). Tell me more: an actionable quality model for Wikipedia. In Proceedings of the 9th International Symposium on Open Collaboration (p. 8). ACM.
- ↑ Halfaker, A. & Warncke-Wang, M., Wiki-Class: Wikipedia article quality classification. docs - repo