About
Develop (personalized) recommendations for the editor dashboard tool, in collaboration with the Editing team. This objective may involve exploring new types of recommendations. (consulting)
Background
As part of PP5, a dashboard (or system) will be designed to surface a subset of backlog of work by community. Such dashboard or system can be a place where recommendations for what to do next can be exposed to editors. To this end, objective 2.2 of TP9 was developed to surface specific type of recommendations developed by Research to interested editors via the dashboard/system.
What kind of recommendations can the research immediately surface in such a dashboard?
- Article recommendation for creation from scratch (with the option of personalization for the user or not)
- Article recommendation for creation via translation (with the option of personalization for the user or not)
- What kind of recommendations can become available for testing in the dashboard?**
It would be really helpful if some space in the dashboard is allocated to experimentation, to surface ongoing research that can become permanent part of the dashboard if successful. To this end, we can start testing certain types of recommendation:
- Article expansion recommendations: we are very close to be able to start testing with section recommendations, for example. On top of that, we are planning to start experiments on image recommendation (for images to be added to articles), infobox content recommendation, etc. (Pau has already provided some designs for section recommendation)
- Hyperlink recommendation (Nirzar and Pau worked on design recommendations for a tool that could surface such recommendations some time ago)
- ...
Subtasks:
- [Leila] Discuss the ideas in more details with Joe
- [Joe] To get back to Leila with a decision whether he sees an opportunity for the dashboard to start surfacing recommendations, starting with recommendations on what article to create next
- [Leila and Joe] Define next steps based on the the decision above.
People:
- @leila
- RS
Dependencies:
- Contributors/Editing
Estimated quarter(s):
- Q1-Q4
Notes:
- In 2015, we ran a large experiment through which we showed that personalized recommendations can increase article creation rate in Wikipedia. In the set-up of the experiment, we showed that such recommendations can increase article recommendations by a factor of 3.2. (Documentation of research and results) Through this research, we know that giving the option to editors to personalize recommendations is important, we also know that recommendations work.