1. Flagged revisions Latest results

2. Summary

Goals 3. Methodology 4. Results 5. Questions and feedback

6. Goals

Study theimpactofflagged revisionsin the editorial work of theGerman Wikipedia .

• Focus onanonymouseditors. 7. Focus onvandalismand reverts.

Questions:

• Is the vandalism from anonymous reduced? 8. Is the number of anonymous blocks reduced? 9. Does it discourage anonymous from editing? 10. Does it decrease number of requests for new accounts? (TODO)

11. Methodology (overview)

Parsepage-logging.xml 12. EDA on the data set.

• Survival analysis on time to review/revert an edit. 13. Numbers and time series:
  • Reverts 14. Blocks /IP-blocks 15. (Semi)-protection 16. Sightedanonymous edits

Comparison with similar versions.

• Polish & Russian(also with flagged-revs) . 17. Also WKP comparable size (FR, IT)

18. Methodology (concepts)

We focus on anonymous contributions. 19. Sighting actions (manual)

• Approved : Revisionsmanuallyflagged asOK . 20. Approved-i : Introduced later to identify first approvals.

Sighting actions (automated)

• Approved-a, approved-ia. 21. Automated approval for trusted editors. 22. Filtered-out.

23. Methodology (approvals) SET OF CONSECUTIVE ANON REVS (page X) r 0 r 1 r 2 r 3 r N-1 r N . . . Pending Pending Pending Pending Pending Pending At first, all revisions in a given series (same page) arepending 24. Methodology (approvals) r 0 r 1 r 2 r 3 r N-1 r N . . . SET OF CONSECUTIVE ANON REVS (page X) Pending Pending Pending Pending Then, we mark all revisions directly approved Approved-direct Approved-direct 25. Methodology (approvals) r 0 r 1 r 2 r 3 r N-1 r N . . . SET OF CONSECUTIVE ANON REVS (page X) Pending Pending Pending All revs in between 2 app-direct are alsoapproved implicitly Approved-direct Approved-direct Approved-implicit 26. Methodology (approvals) r 0 r 1 r 2 r 3 r N-1 r N . . . SET OF CONSECUTIVE ANON REVS (page X) Approved-implicit Approved-implicit Approved-direct Pending Approved-direct Approved-implicit All revs before direct approval are alsoapproved implicitly 27. Methodology (reverts)

Vandalreverts

• Identified by regexps. 28. Does not include standard admin reverts.

Otherreverts.

• Reverts without explicit reference to vandalism 29. Includes admin reverts.

30. Methodology (reverts)

Detecting reverted revisions

• First, look for the newest revision with the same size (after revert action). 31. From that on, mark as reverted all consecutive revisions performed by same IP. 32. If that fails, look for IP info in the comment field, and look for newest revision performed by that IP. 33. Then, same procedure to mark all consecutive revisions.

Feedback?

34. RESULTS 35. Evolution anonymous edits 36. Evol anonymous edits (focus) 37. Evolution review actions 38. Time to approve/revert revisions r 0 r 1 r 2 r 3 r N-1 r N . . . SET OF CONSECUTIVE ANON REVS (page X) tstamp(r N-1 ) -tstamp(r 1 ) Anon-user Logged user Logged user Logged user Logged user ->Approve r 1 Logged user 39. Time to approve/revert revisions Revisions approved orReverted at a very fast pace 40. Truth in numbers

Revert actions performed at very fast pace.

• Revert(median) : 48 min. 41. Revert-v(median) :36 seg . ()

High number of actions registered ->accuracy

events *rmean *se(rmean)median 0.95LCL 0.95UCL Status=1 2892231241.80.5783.3693.345 3.3933 Status=2 1839583988.01.442 194.082 193.445194.7781 Status=33177451.00.7440.8070.7560.8700 Status=411963210.90.1680.0100.0100.0103 1 = Approved-d ; 2 = Approved-im ; 3 = revert ; 4 = revert-v 42. Comments on time to app/revert

Implications

• Looks like extremely fast pace for acting on revisions. 43. Community takes this new role very seriosly. 44. Provides stronger incentive to watch content even closely.

45. Evolution % reverted edits Some reverts in the red line could belong to the black one 46. Evolution % editors who revert 47. Evolution blocked users 48. Evolution of protection actions 49. Conclusions

In general, flagged revisions did not affected the anonymous editing.

• Most revisions got approved very rapidly

More activity on vandalism reverts.

• Even faster than approval actions.

Reduced impact of vandalism.

• Growing number of reverts. 50. On an increasing number of pages.

Mandatory comments had much more direct influence.

51. Open questions / feedback

Q: What did happen at the beginning of 2008 for such a high number of user pages protected?

• A: mass-blocking of open proxies.
  • Creating the user page of blocked IPs with a template and protecting them.

We need patterns for detecting reverts:

• Russian Wikipedia 52. Polish Wikipedia

Comments and feedback are very welcome.