However, measuring productivity by the difference of the times of first and last edits won't do much for those of us who work on pages for hours before pressing the save button and only save once. (: It also doesn't measure time spent on private wikis or discussions on email and IRC, which also are not countable as productivity if you look only at public edit counts and logged actions.
I'm assuming that login and logout times on all wikis are not available for research use. If they were there would be privacy issues although mitigation is possible. Pine From: aaron.halfa...@gmail.com Date: Fri, 7 Feb 2014 17:15:36 -0600 To: wiki-research-l@lists.wikimedia.org Subject: Re: [Wiki-research-l] Preexsiting Researchers on Metrics for Users? I talked to Max on IRC, but I'm pointing here for the lurkers :) I think that measuring labor hours via edit sessions is a great idea and I have python library to help extract sessions from edit histories. See https://bitbucket.org/halfak/mediawiki-utilities. Assuming that you have a list of a user's revisions from the API, using the session extractor to build a set of session start and end timestamps for a user would look like this: ----------------------------from mwutil.lib import sessions # Get your revisions ordered by timestamp# revisions = <some API call result> events = (rev['user'], rev['timestamp'], rev) for rev in revisions for user, session in sessions.sessions(events): # write out a TSV file print "\t".join( str(v) for v in [user, len(session), session[0]['timestamp'], session[-1]['timestamp'] )--------------------------- On Fri, Feb 7, 2014 at 12:25 PM, Klein,Max <kle...@oclc.org> wrote: Thanks Nemo, I'll re-read that discussion. I think that conversation is where I became tentative of using bytes or edit counts. Aaron, in my own search I also noticed you wrote with Geiger. About counting edit hour and edit sessions. [1] Calculating content persistence is a bit too heavyweight for me right now since I am trying to submit to ACM Web Science in 2 weeks (hose CFP was just on this list). The technique looks great though, and I would like to help support making a WMFlabs tool that can return this measure. It seems like I could calculate approximate edit-hours from just looking at Special:Contributions timestamps. Is that correct? Would you suggest this route? [1] http://www-users.cs.umn.edu/~halfak/publications/Using_Edit_Sessions_to_Measure_Participation_in_Wikipedia/geiger13using-preprint.pdf Maximilian Klein Wikipedian in Residence, OCLC +17074787023 From: wiki-research-l-boun...@lists.wikimedia.org <wiki-research-l-boun...@lists.wikimedia.org> on behalf of Aaron Halfaker <aaron.halfa...@gmail.com> Sent: Friday, February 07, 2014 7:12 AM To: Research into Wikimedia content and communities Subject: Re: [Wiki-research-l] Preexsiting Researchers on Metrics for Users? Hey Max, There's a class of metrics that might be relevant to your purposes. I refer to them as "content persistence" metrics and wrote up some docs about how they work including an example. See https://meta.wikimedia.org/wiki/Research:Content_persistence. I gathered a list of papers below to provide a starting point. I've included links to open access versions where I could. These metrics are a little bit painful to compute due to the computational complexity of diffs, but I have some hardware to throw at the problem and another project that's bringing me in this direction, so I'd be interested in collaborating. Priedhorsky, Reid, et al. "Creating, destroying, and restoring value in Wikipedia." Proceedings of the 2007 international ACM conference on Supporting group work. ACM, 2007. http://reidster.net/pubs/group282-priedhorsky.pdf: Describes "Persistent word views" which is a measure of value added per editor. (IMO, value actualized) B. Thomas Adler, Krishnendu Chatterjee, Luca de Alfaro, Marco Faella, Ian Pye, and Vishwanath Raman. 2008. Assigning trust to Wikipedia content. In Proceedings of the 4th International Symposium on Wikis (WikiSym '08). ACM, New York, NY, USA, , Article 26 , 12 pages. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.141.2047&rep=rep1&type=pdf Describes a complex strategy for assigning trustworthiness to content based on implicit review. See http://wikitrust.soe.ucsc.edu/ Halfaker, A., Kittur, A., Kraut, R., & Riedl, J. (2009, October). A jury of your peers: quality, experience and ownership in Wikipedia. In Proceedings of the 5th International Symposium on Wikis and Open Collaboration (p. 15). ACM. http://www-users.cs.umn.edu/~halfak/publications/A_Jury_of_Your_Peers/halfaker09jury-personal.pdf Describes the use of "Persistent word revisions per word" as a measure of article contribution quality. Halfaker, A., Kittur, A., & Riedl, J. (2011, October). Don't bite the newbies: how reverts affect the quantity and quality of Wikipedia work. In Proceedings of the 7th International Symposium on Wikis and Open Collaboration (pp. 163-172). ACM. http://www-users.cs.umn.edu/~halfak/publications/Don't_Bite_the_Newbies/halfaker11bite-personal.pdf Describes the use of raw "Persistent work revisions" as a measure of editor productivity Looking back on the study, I think I'd rather use log(# of revisions a word persists) * words. -Aaron On Fri, Feb 7, 2014 at 1:48 AM, Federico Leva (Nemo) <nemow...@gmail.com> wrote: Sort of related, an ongoing education@ discussion "student evaluation criteria". http://thread.gmane.org/gmane.org.wikimedia.education/854 Nemo _______________________________________________ Wiki-research-l mailing list Wiki-research-l@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/wiki-research-l _______________________________________________ Wiki-research-l mailing list Wiki-research-l@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/wiki-research-l _______________________________________________ Wiki-research-l mailing list Wiki-research-l@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
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