Artificial Intelligence Aims to Make Wikipedia Friendlier and Better
The nonprofit behind Wikipedia is turning to machine learning to combat a long-standing decline in the number of editors.
Tom Simonite | November 30, 2015
One motivation for the project is a significant decline in the number of people considered active contributors to the flagship English-language Wikipedia: it has fallen by 40 percent over the past eight years, to about 30,000. Research indicates that the problem is rooted in Wikipedians’ complex bureaucracy and their often hard-line responses to newcomers’ mistakes, enabled by semi-automated tools that make deleting new changes easy (see “The Decline of Wikipedia”).
The Objective Revision Evaluation Service (ORES) is a web service running in Wikimedia Labs that provides machine learning as a service for Wikimedia Projects. The system is designed to help automate critical wiki-work -- for example, vandalism detection and removal. This service is developed as part of the R:Revision scoring as a service project.By keeping contribution open, but being good at quality control, open knowledge projects maximize productivity and quality -- and this works for large wikis that are well supported by quality control tools (e.g. English and German Wikipedia), but remain a burden for small wikis. ORES is intended to provide a generalized service to support quality control and curation work in all wikis.
<more at http://www.technologyreview.com/news/544036/artificial-intelligence-aims-to-make-wikipedia-friendlier-and-better/; related links: http://www.technologyreview.com/featuredstory/520446/the-decline-of-wikipedia/ (The Decline of Wikipedia. October 22, 2013) and (Wikipedia: Objective Revision Evaluation Service) and http://www.wired.com/2015/12/wikipedia-is-using-ai-to-expand-the-ranks-of-human-editors/ (Wikipedia Deployes AI to Expand Its Ranks of Human Editors. December 1, 2015)>
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