We just published an announcement on the Wikimedia blog marking the official launch of revision scoring as a service https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service and I wanted to say a few words about this project:
Blog post: https://blog.wikimedia.org/2015/11/30/artificial-intelligence-x-ray-specs/ https://blog.wikimedia.org/2015/11/30/artificial-intelligence-x-ray-specs/ Docs on Meta: https://meta.wikimedia.org/wiki/ORES https://meta.wikimedia.org/wiki/ORES
First off: what’s revision scoring https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Rationale? On the surface, it’s a set of open APIs allowing you to automatically “score” any edit and measure their probability of being damaging or good-faith contributions. The real goal behind this project, though, is to fix the damage indirectly caused by vandal-fighting bots and tools on good-faith contributors and to bring back a collaborative dimension to how we do quality control on Wikipedia. I invite you to read the whole blog post https://blog.wikimedia.org/2015/11/30/artificial-intelligence-x-ray-specs/ if you want to know more about the motivations and expected outcome of this project.
I am thrilled this project is coming to fruition and I’d like to congratulate Aaron Halfaker https://wikimediafoundation.org/wiki/User:Ahalfaker and all the project contributors https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Team on hitting this big milestone: revision scoring started as Aaron’s side project well over a year ago and it has been co-designed (as in – literally – conceived, implemented, tested, improved and finally adopted) by a distributed team of volunteer developers, editors, and researchers. We worked with volunteers in 14 different Wikipedia language editions and as of today revision scores are integrated https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Tools_that_use_ORES in the workflow of several quality control interfaces, WikiProjects and 3rd party tools. The project would not have seen the light without the technical support provided by the TechOps team (Yuvi in particular) and seminal funding provided by the WMF IEG program and Wikimedia Germany.
So, here you go: the next time someone tells you that LLAMAS GROW ON TREES https://en.wikipedia.org/w/index.php?diff=prev&oldid=642215410 you can confidently tell them they should stop damaging http://ores.wmflabs.org/scores/enwiki/damaging/642215410/ Wikipedia.
Dario
Dario Taraborelli Head of Research, Wikimedia Foundation wikimediafoundation.org http://wikimediafoundation.org/ • nitens.org http://nitens.org/ • @readermeter http://twitter.com/readermeter
Super !
Congratulation!
Nicolas
Le 01/12/2015 02:27, Dario Taraborelli a écrit :
We just published an announcement on the Wikimedia blog marking the official launch of revision scoring as a service https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service and I wanted to say a few words about this project:
Blog post: https://blog.wikimedia.org/2015/11/30/artificial-intelligence-x-ray-specs/ Docs on Meta: https://meta.wikimedia.org/wiki/ORES
First off: what’s revision scoring https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Rationale? On the surface, it’s a set of open APIs allowing you to automatically “score” any edit and measure their probability of being damaging or good-faith contributions. The real goal behind this project, though, is to fix the damage indirectly caused by vandal-fighting bots and tools on good-faith contributors and to bring back a collaborative dimension to how we do quality control on Wikipedia. I invite you to read the whole blog post https://blog.wikimedia.org/2015/11/30/artificial-intelligence-x-ray-specs/ if you want to know more about the motivations and expected outcome of this project.
I am thrilled this project is coming to fruition and I’d like to congratulate Aaron Halfaker https://wikimediafoundation.org/wiki/User:Ahalfaker and all the project contributors https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Team on hitting this big milestone: revision scoring started as Aaron’s side project well over a year ago and it has been co-designed (as in – literally – conceived, implemented, tested, improved and finally adopted) by a distributed team of volunteer developers, editors, and researchers. We worked with volunteers in 14 different Wikipedia language editions and as of today revision scores are integrated https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Tools_that_use_ORES in the workflow of several quality control interfaces, WikiProjects and 3rd party tools. The project would not have seen the light without the technical support provided by the TechOps team (Yuvi in particular) and seminal funding provided by the WMF IEG program and Wikimedia Germany.
So, here you go: the next time someone tells you that LLAMAS GROW ON TREES https://en.wikipedia.org/w/index.php?diff=prev&oldid=642215410 you can confidently tell them they should stop damaging http://ores.wmflabs.org/scores/enwiki/damaging/642215410/ Wikipedia.
Dario
*Dario Taraborelli *Head of Research,Wikimedia Foundation wikimediafoundation.org http://wikimediafoundation.org/• nitens.org http://nitens.org/ • @readermeter http://twitter.com/readermeter
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I see that the upcoming Metrics Meeting will include a research presentation about the Teahouse. Any chance of having ORES presented at the January Metrics Meeting? :)
On Mon, Nov 30, 2015 at 5:27 PM, Dario Taraborelli < dtaraborelli@wikimedia.org> wrote:
We just published an announcement on the Wikimedia blog marking the official launch of revision scoring as a service https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service and I wanted to say a few words about this project:
Blog post: https://blog.wikimedia.org/2015/11/30/artificial-intelligence-x-ray-specs/ Docs on Meta: https://meta.wikimedia.org/wiki/ORES
First off: what’s revision scoring https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Rationale? On the surface, it’s a set of open APIs allowing you to automatically “score” any edit and measure their probability of being damaging or good-faith contributions. The real goal behind this project, though, is to fix the damage indirectly caused by vandal-fighting bots and tools on good-faith contributors and to bring back a collaborative dimension to how we do quality control on Wikipedia. I invite you to read the whole blog post https://blog.wikimedia.org/2015/11/30/artificial-intelligence-x-ray-specs/ if you want to know more about the motivations and expected outcome of this project.
I am thrilled this project is coming to fruition and I’d like to congratulate Aaron Halfaker https://wikimediafoundation.org/wiki/User:Ahalfaker and all the project contributors https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Team on hitting this big milestone: revision scoring started as Aaron’s side project well over a year ago and it has been co-designed (as in – literally – conceived, implemented, tested, improved and finally adopted) by a distributed team of volunteer developers, editors, and researchers. We worked with volunteers in 14 different Wikipedia language editions and as of today revision scores are integrated https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Tools_that_use_ORES in the workflow of several quality control interfaces, WikiProjects and 3rd party tools. The project would not have seen the light without the technical support provided by the TechOps team (Yuvi in particular) and seminal funding provided by the WMF IEG program and Wikimedia Germany.
So, here you go: the next time someone tells you that LLAMAS GROW ON TREES https://en.wikipedia.org/w/index.php?diff=prev&oldid=642215410 you can confidently tell them they should stop damaging http://ores.wmflabs.org/scores/enwiki/damaging/642215410/ Wikipedia.
Dario
*Dario Taraborelli *Head of Research, Wikimedia Foundation wikimediafoundation.org • nitens.org • @readermeter http://twitter.com/readermeter
Analytics mailing list Analytics@lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics
Oooh! That sounds like a good idea. Fun story: I presented the idea and the proof of concept service at the metrics meeting last January. :)
I'll look into it. Thanks for the suggestion Pine.
On Tue, Dec 1, 2015 at 2:16 PM, Pine W wiki.pine@gmail.com wrote:
I see that the upcoming Metrics Meeting will include a research presentation about the Teahouse. Any chance of having ORES presented at the January Metrics Meeting? :)
On Mon, Nov 30, 2015 at 5:27 PM, Dario Taraborelli < dtaraborelli@wikimedia.org> wrote:
We just published an announcement on the Wikimedia blog marking the official launch of revision scoring as a service https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service and I wanted to say a few words about this project:
Blog post: https://blog.wikimedia.org/2015/11/30/artificial-intelligence-x-ray-specs/ Docs on Meta: https://meta.wikimedia.org/wiki/ORES
First off: what’s revision scoring https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Rationale? On the surface, it’s a set of open APIs allowing you to automatically “score” any edit and measure their probability of being damaging or good-faith contributions. The real goal behind this project, though, is to fix the damage indirectly caused by vandal-fighting bots and tools on good-faith contributors and to bring back a collaborative dimension to how we do quality control on Wikipedia. I invite you to read the whole blog post https://blog.wikimedia.org/2015/11/30/artificial-intelligence-x-ray-specs/ if you want to know more about the motivations and expected outcome of this project.
I am thrilled this project is coming to fruition and I’d like to congratulate Aaron Halfaker https://wikimediafoundation.org/wiki/User:Ahalfaker and all the project contributors https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Team on hitting this big milestone: revision scoring started as Aaron’s side project well over a year ago and it has been co-designed (as in – literally – conceived, implemented, tested, improved and finally adopted) by a distributed team of volunteer developers, editors, and researchers. We worked with volunteers in 14 different Wikipedia language editions and as of today revision scores are integrated https://meta.wikimedia.org/wiki/Research:Revision_scoring_as_a_service#Tools_that_use_ORES in the workflow of several quality control interfaces, WikiProjects and 3rd party tools. The project would not have seen the light without the technical support provided by the TechOps team (Yuvi in particular) and seminal funding provided by the WMF IEG program and Wikimedia Germany.
So, here you go: the next time someone tells you that LLAMAS GROW ON TREES https://en.wikipedia.org/w/index.php?diff=prev&oldid=642215410 you can confidently tell them they should stop damaging http://ores.wmflabs.org/scores/enwiki/damaging/642215410/ Wikipedia.
Dario
*Dario Taraborelli *Head of Research, Wikimedia Foundation wikimediafoundation.org • nitens.org • @readermeter http://twitter.com/readermeter
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