+1 I've been working with James Hare (WikiProject X) to use the revision scoring system to support their work. Their bot is actually pulling scores from our service right now. :)
Also +1 for Wikiprojects as entry points for newcomers. I've been pitching a WikiProject recommender service for a while. I'd really like to start experimenting with that. I think that might have been one of the next logical steps for the Growth team if it was still around. -Aaron On Mon, Aug 3, 2015 at 1:46 PM, Pine W <[email protected]> wrote: > Hi Aaron, > > Thanks, those sound like good ideas for better quality control and > mentoring/socialization pathways. > > Are there opportunities to coordinate your work on counter-vandalism tools > and empowering wikiprojects into the work that others are doing with > wikiprojects, such as "Wikiproject X > <https://en.wikipedia.org/wiki/Wikipedia:WikiProject_X>" and Michael > Gilbert's work that he recently mentioned on the Analytics mailing list? > > One of my thoughts is that it would be good to encourage newcomers to get > involved with active wikiprojects very early in their Wikipedia careers, to > get guidance and to develop friendships that might increase editor > retention. > > Thanks! > > Pine > > Pine > > > On Mon, Aug 3, 2015 at 8:10 AM, Aaron Halfaker <[email protected]> > wrote: > >> Hey folks, >> >> I'm glad the presentation came across so well. I really appreciate the >> discussion. >> >> Pine, I really appreciate those plots that you linked. It seems that you >> can identify the progression through barrier types by following the >> hexagonal graphs clockwise. Concerns start with complex rules and (to a >> lesser extend) the difficulty of editing and progress to concerns negative >> social behavior and access to reference materials. >> >> Regarding editathons, I'm not quite sure the right way to measure their >> effects. I suspect that one of the biggest effects of editathons are the >> result of discussions that people have with their friends and family after >> the event. "I edited Wikipedia and it was fun. It turns out that there's >> a lot of different types of ways to contribute. You don't have to be an >> expert." -- is a conversation I imagine is relatively common after an >> editathon. The awareness (I can edit Wikipedia?!), new registrations and >> contributions that result from such once-removed discussions would be >> nearly impossible to track. >> >> Jane, seem more of my work exploring the rising social/motivational >> barriers here: https://www.youtube.com/watch?v=bozyc1z25aQ#t=24m49s In >> the conclusion of that talk, I bring up Snuggle[1] as an example of a >> technological strategy for supporting desirable social behaviors. My >> recent work on the Revision Scoring[2] was originally inspired by my work >> to extend Snuggle beyond English Wikipedia -- I needed vandalism prediction >> scores beyond English Wikipedia! Generally, I think we (as Wikipedian >> community members) have a lot deeper insight into the types of behaviors >> (e.g. reactions to newcomer contributions) that are desirable than we had >> in 2006 and that, if we were to redesign counter-vandalism tools from >> scratch with these insights in mind, we'd be able to dramatically reduce >> this type of social/motivational barrier. I think Snuggle is a good >> example of such a new type of tool and the idea with Revision Scoring is >> that I'd like to make it *really easy* for others to experiment with their >> own strategies. The next thing I want to do is to try empowering >> WikiProjects with automated quality control/socialization tools. I suspect >> that, WikiProject members will be highly motivated to socialize potential >> good newcomers and help them work productively within the topical context >> of their WikiProject -- if they had the means to do so efficiently. >> >> 1. https://en.wikipedia.org/wiki/Wikipedia:Snuggle >> 2. https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service >> >> -Aaron >> >> On Mon, Aug 3, 2015 at 7:36 AM, Jane Darnell <[email protected]> wrote: >> >>> OK I am replying to this mail, as this one has the link to Youtube in it >>> with the two presentations. I am only responding to the first presentation >>> by Aaron here. >>> >>> In general I like the idea of focussing attention on the "New Editor >>> Activation Funnel". This area is of course the reason why we have a decline >>> in new editors, and it all has to do with an increase in "barriers to >>> entry" (which btw I am not convinced is the same thing as "technical >>> impediments"). It is useful to split these barriers up into Permission, >>> Literacy (here wikimarkup is lumped together with policies), and >>> Social/Motivational (human interaction) issues, but I think the whole >>> presentation misses the point on the need for more dissection of the >>> reverts problem (shown a bit towards the end). >>> >>> I personally think that demotivational behavior by experienced >>> Wikipedians is the biggest factor in the decline of new editor >>> contributions, but unlike most people I don't think this has to do with >>> what the experienced Wikipedians do, but rather what they don't do. They >>> don't welcome people in person (because they don't see their edits) and >>> they don't give timely feedback on first edits to pages on their watchlist >>> (no way to see if those edits are first time edits). They don't show them >>> the ropes in that if one wants to make a BLP, or an article about a company >>> or building or place, or an article about an artwork, you should look at >>> existing examples and start from there. Having said this, I do think we >>> spend an inordinate amount of time on things like extending the page about >>> WHAT WIKIPEDIA IS NOT (which btw I have yet to read). It seems that our >>> best way of dealing with newcomers is to throw CAPS at them, though we all >>> hate CAPS. >>> >>> The point of this study was to prove these two: H1: VE will increase the >>> amount of desirable edits by newbies and H2: VE will increase the amount of >>> undesirable edits by newbies (aka VANDALISM). Guess what? Both H1 & H2 show >>> no significance and if anything, less vandalism came from VE editors. I >>> could have told you that beforehand - yawn. It angers me when people assume >>> that others are not technical enough for Wikipedia. Sorry, but it is not >>> rocket science. >>> >>> This type of thinking is not just on Wikipedia, I see this also in >>> health occupations, where doctors tell their patients not to go look things >>> up on the Internet. Just trust the doctors because they studied it! Yeah >>> right, like I am going to trust all aspects of my future health and >>> well-being to someone who sees my future health and well-being as a >>> 10-minute interlude in their 9-5 workday. No, I will nod politely (one must >>> always remain friendly) while googling my way to better health, thanks. And >>> if I want to make an article about something that I think needs an article >>> on Wikipedia, I am going to try to do it on my own as far as I can get, and >>> I am probably not interested in talking about it until I am done. The whole >>> AfC queue thing is absolutely horrible because it puts these edits on ice >>> until the person totally forgets what the password was that they dreamed up >>> for their user account. As far as spelling corrections go, if I correct an >>> error and see it deleted (like from Kiev to Kyiv, which will be reverted by >>> a bot probably), then I will probably not come back. >>> >>> I am very eager to hear more about the revision scoring though! I wish >>> there was a better way to do that than manually however. >>> Jane >>> >>> On Wed, Jul 29, 2015 at 8:07 PM, Leila Zia <[email protected]> wrote: >>> >>>> A friendly reminder that this is happening in 23 min. :-) >>>> >>>> YouTube stream: https://www.youtube.com/watch?v=vGyrVg_qKSM >>>> IRC: #wikimedia-research >>>> >>>> Best, >>>> Leila >>>> >>>> On Mon, Jul 27, 2015 at 2:47 PM, Leila Zia <[email protected]> wrote: >>>> >>>>> Hi everyone, >>>>> >>>>> The next Research showcase will be live-streamed this Wednesday, July >>>>> 29 at 11.30 PT. The streaming link will be posted on the lists a few >>>>> minutes before the showcase starts (sorry, we haven't been able to solve >>>>> this, yet. :-() and as usual, you can join the conversation on IRC at >>>>> #wikimedia-research. >>>>> >>>>> We look forward to seeing you! >>>>> >>>>> Leila >>>>> >>>>> >>>>> This month: >>>>> *VisualEditor's effect on newly registered users*By *Aaron Halfaker* >>>>> <https://www.mediawiki.org/wiki/User:Halfak_%28WMF%29> >>>>> >>>>> It's been nearly two years since we ran an initial study >>>>> <https://meta.wikimedia.org/wiki/Research:VisualEditor%27s_effect_on_newly_registered_editors/June_2013_study> >>>>> of VisualEditor's effect on newly registered editors. While most of >>>>> the results of this study were positive (e.g. workload on Wikipedians >>>>> did not increase), we still saw a significant decrease in the newcomer >>>>> productivity. In the meantime, the Editing >>>>> <https://www.mediawiki.org/wiki/Editing> team has made substantial >>>>> improvements to performance and functionality. In this presentation, I'll >>>>> report on the results of a new experiment designed to test the effects of >>>>> enabling this improved VisualEditor software for newly registered >>>>> users by default. I'll show what we learned from the experiment and >>>>> discuss >>>>> some results have opened larger questions about what, exactly, is >>>>> difficult >>>>> about being a newcomer to English Wikipedia. >>>>> >>>>> *Wikipedia knowledge graph with DeepDive* >>>>> By *Juhana Kangaspunta* and >>>>> *Thomas Palomares (10-week student project)* >>>>> Despite the tremendous amount of information present on Wikipedia, >>>>> only a very little amount is structured. Most of the information is >>>>> embedded in text and extracting it is a non-trivial challenge. In this >>>>> project, we try to populate Wikidata, a structured component of >>>>> Wikipedia, using DeepDive tool to extract relations embedded in the >>>>> text. We finally extracted more than 140,000 relations with more than 90% >>>>> average precision. We will present DeepDive and the data that we use >>>>> for this project, we explain the relations we focused on so far and >>>>> explain >>>>> the implementation and pipeline, including our model, features and >>>>> extractors. Finally, we detail our results with a thorough precision and >>>>> recall analysis. >>>>> >>>> >>>> >>>> _______________________________________________ >>>> Wiki-research-l mailing list >>>> [email protected] >>>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l >>>> >>>> >>> >>> _______________________________________________ >>> Wiki-research-l mailing list >>> [email protected] >>> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l >>> >>> >> >> _______________________________________________ >> Wiki-research-l mailing list >> [email protected] >> https://lists.wikimedia.org/mailman/listinfo/wiki-research-l >> >> > > _______________________________________________ > Wiki-research-l mailing list > [email protected] > https://lists.wikimedia.org/mailman/listinfo/wiki-research-l > >
_______________________________________________ Wiki-research-l mailing list [email protected] https://lists.wikimedia.org/mailman/listinfo/wiki-research-l
