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SUMMARY:A Theoretical Analysis of Crowdsourced Content Curation  - Greg St
 oddard (Northwestern)
DTSTART:20121105T150000Z
DTEND:20121105T160000Z
UID:TALK41238@talks.cam.ac.uk
CONTACT:Felix Fischer
DESCRIPTION:Today\, the internet is flooded with vast quantities of conten
 t created both by professionals and amatuers. To cope with this informatio
 n overload\, users seek the help of curators to recommend which content to
  consume. The two most common forms of curation are expert-based\, the edi
 tor of a newspaper decides which articles to place on the front page\, and
  algorithmic-based\, a search algorithm determining the ranking of website
 s for a given query. In recent years\, content aggregators which use expli
 cit vote-based feedback from users to curate content for future users have
  grown exponentially in popularity. The goal of this paper is to provide a
  descriptive analysis of _crowd-sourced curation mechanisms_.   \n\nIn par
 ticular\, we study crowd-curation mechanisms that rank articles according 
 to a score which is a function of user-feedback. We quantify the extent to
  which the highly promoted articles of a crowd-curator actually represent 
 the preferences of the user population. While crowd-curation can be relati
 vely effective for cardinal objectives like discovering and promoting cont
 ent of high quality\, they do not perform well for ordinal objectives such
  as finding the best articles. Our analysis suggests that user preferences
  and behavior are a far greater determinant of curation quality than the a
 ctual details of the curation mechanism. Finally\, we show that certain sh
 ifts in user voting behavior can have positive impacts on these systems\, 
 suggesting that active moderation of user behavior is important for high q
 uality curation in crowd-sourced systems. \n\nThis is joint work with Yorg
 os Askalidis. 
LOCATION:MR12\, Centre for Mathematical Sciences\, Wilberforce Road\, Camb
 ridge
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