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A bird’s eye view of editor activation
Dario Taraborelli
Wikimedia Research and Data showcase
May 2014
Activation
m:Research:Editor_activation
m:Research:New_editor
Why does it matter
The vast majority of newly registered users never edit.
Help estimate the ceiling of new editor engagem...
1. longitudinal data
2. mobile vs desktop activation
24h activation rates for newly registered users (desktop vs mobile registrations) [source]
30-day activation rates for newly registered users (desktop vs mobile registrations) [source]
3. segmenting newly registered users
internal referral
https://meta.wikimedia.org/wiki/Schema:ServerSideAccountCreation
30-day desktop account activation by referral type (source - data)
30-day mobile account activation by referral type (source - data)
What’s missing
Qualitative analysis on the type of contributions made by different
subpopulations of new users.
Better und...
Takeaways
New users are not created equal
Some projects have higher activation rates than English Wikipedia.
Some projects...
Questions?
dario@wikimedia.org
Read more
https://meta.wikimedia.org/wiki/Research:Metrics_standardization
Image credits
Kr...
A bird's eye view of Wikipedia's new editor activation
A bird's eye view of Wikipedia's new editor activation
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A high-level overview of differences in activation and engagement among newly registered users on Wikipedia.

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A bird's eye view of Wikipedia's new editor activation

  1. 1. A bird’s eye view of editor activation Dario Taraborelli Wikimedia Research and Data showcase May 2014
  2. 2. Activation m:Research:Editor_activation m:Research:New_editor
  3. 3. Why does it matter The vast majority of newly registered users never edit. Help estimate the ceiling of new editor engagement. Help discover highly engaged populations of new users.
  4. 4. 1. longitudinal data
  5. 5. 2. mobile vs desktop activation
  6. 6. 24h activation rates for newly registered users (desktop vs mobile registrations) [source]
  7. 7. 30-day activation rates for newly registered users (desktop vs mobile registrations) [source]
  8. 8. 3. segmenting newly registered users
  9. 9. internal referral https://meta.wikimedia.org/wiki/Schema:ServerSideAccountCreation
  10. 10. 30-day desktop account activation by referral type (source - data)
  11. 11. 30-day mobile account activation by referral type (source - data)
  12. 12. What’s missing Qualitative analysis on the type of contributions made by different subpopulations of new users. Better understanding of drop-off rates at specific steps in the edit funnel.
  13. 13. Takeaways New users are not created equal Some projects have higher activation rates than English Wikipedia. Some projects show an upward trend in net new editors, compared to English Wikipedia. We should target specific populations of new users, the majority of new users coming from generic referrals are significantly less engaged.
  14. 14. Questions? dario@wikimedia.org Read more https://meta.wikimedia.org/wiki/Research:Metrics_standardization Image credits Kristina Alexanderson, On top of my head https://www.flickr.com/photos/kalexanderson/6140989346
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    May. 21, 2014

A high-level overview of differences in activation and engagement among newly registered users on Wikipedia.

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