Everyone counts? Design considerations in online citizen science

被引：41

作者：

Spiers, Helen ^{[1
,2
]}

Swanson, Alexandra ^{[3
,4
]}

Fortson, Lucy ^{[5
]}

Simmons, Brooke D. ^{[6
,7
]}

Trouille, Laura ^{[8
,9
,10
]}

Blickhan, Samantha ^{[9
,11
,12
]}

Lintott, Chris ^{[7
,9
,13
,14
]}

机构：

[1] Univ Oxford, Zooniverse Citizen Sci Platform, Oxford, England

[2] Univ Oxford, Dept Astrophys, Oxford, England

[3] Zooniverse, Ecol Initiat, Oxford, England

[4] AAAS Sci & Technol Policy, Wildlife Conservat Policy Issues, Washington, DC USA

[5] Univ Minnesota, Phys, Minneapolis, MN 55455 USA

[6] Univ Lancaster, Phys, Lancaster, England

[7] Galaxy Zoo, Oxford, England

[8] Adler Planetarium, Citizen Sci, Chicago, IL USA

[9] Zooniverse, Oxford, England

[10] Northwestern Univ, Evanston, IL 60208 USA

[11] IMLS, Washington, DC USA

[12] Adler Planetarium, Chicago, IL USA

[13] Univ Oxford, Astrophys, Oxford, England

[14] New Coll, Oxford, England

来源：

JCOM-JOURNAL OF SCIENCE COMMUNICATION | 2019年 / 18卷 / 01期

关键词：

Citizen science; Public engagement with science and technology; Social inclusion; GOOGLE ANALYTICS; DIVERSITY; PERFORMANCE;

D O I：

10.22323/2.18010204

中图分类号：

G2 [信息与知识传播];

学科分类号：

05 ; 0503 ;

摘要：

Effective classification of large datasets is a ubiquitous challenge across multiple knowledge domains. One solution gaining in popularity is to perform distributed data analysis via online citizen science platforms, such as the Zooniverse. The resulting growth in project numbers is increasing the need to improve understanding of the volunteer experience; as the sustainability of citizen science is dependent on our ability to design for engagement and usability. Here, we examine volunteer interaction with 63 projects, representing the most comprehensive collection of online citizen science project data gathered to date. Together, this analysis demonstrates how subtle project design changes can influence many facets of volunteer interaction, including when and how much volunteers interact, and, importantly, who participates. Our findings highlight the tension between designing for social good and broad community engagement, versus optimizing for scientific and analytical efficiency.

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