Crowdsourcing, attention and productivity

被引：121

作者：

Huberman, Bernardo A. ^{[1
]}

Romero, Daniel M. ^{[2
]}

Wu, Fang ^{[1
]}

机构：

[1] HP Labs, Social Comp Lab, Palo Alto, CA USA

[2] Cornell Univ, Ctr Appl Math, Ithaca, NY 14853 USA

来源：

JOURNAL OF INFORMATION SCIENCE | 2009年 / 35卷 / 06期

关键词：

crowdsourcing; social attention; MODELS;

D O I：

10.1177/0165551509346786

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

080201 [机械制造及其自动化];

摘要：

We show through an analysis of a massive data set from YouTube that the productivity exhibited in crowd-sourcing 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.

引用

页码：758 / 765

页数：8

共 16 条

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Breast cancer screening with mammography [J].