Publication | Closed Access
Crowdsourcing, attention and productivity
264
Citations
13
References
2009
Year
EngineeringEmerging MediaCommunicationProductivityComputational Social ScienceSocial MediaData ScienceContent AnalysisShort-term ContributorsHuman ComputationMassive Data SetUser-generated ContentMedia DistributionVideo ContentDigital MediaInformation ManagementCrowdsourcingCrowd ComputingSocial ComputingHuman-computer InteractionKnowledge ManagementOwn MediaArtsSocietal Implications
We show through an analysis of a massive data set from YouTube that the productivity exhibited in crowdsourcing exhibits a strong positive dependence on attention, measured by the number of downloads. Conversely, a lack of attention leads to a decrease in the number of videos uploaded and the consequent drop in productivity, which in many cases asymptotes to no uploads whatsoever. Moreover, short-term contributors compare their performance to the average contributor’s performance while long-term contributors compare it to their own media.
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