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It’s All News to Me: The Remix

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dc.contributor.author Boon, Miriam
dc.date.accessioned 2017-12-28T00:52:26Z
dc.date.available 2017-12-28T00:52:26Z
dc.date.issued 2018-01-03
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/50101
dc.description.abstract This paper examines the automation of editorial curation of online news and blog articles based on reader ratings. Websites usually provide no guidelines on how to evaluate and rate articles; the NewsTrust project explores how doing so could improve rating precision. Building on and expanding from existing, but incomplete, research, I describe simulations of article comparison to determine how many reader ratings are necessary to distinguish between articles.
dc.format.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Collective Intelligence and Crowds
dc.subject crowdsourcing, user ratings, journalism
dc.title It’s All News to Me: The Remix
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2018.214
Appears in Collections: Collective Intelligence and Crowds


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