Title
A proposed genome of mobile and situated crowdsourcing and its design implications for encouraging contributions.
Abstract
A number of papers have surveyed mobile crowdsourcing systems and, to a lesser extent, situated crowdsourcing systems. These surveys have either contributed a comprehensive taxonomy of the diverse application domains where the systems have tapped into or have characterized different components of the system platforms. In this paper, we present a survey of mobile and situated crowdsourcing systems by addressing fundamental questions about user contributions that system designers pose when building new systems or evaluating existing ones. We select and analyze 40 mobile and situated crowdsourcing systems for which prototypes were deployed and studied in the real world. Inspired by the MIT's genetic model of collective intelligence, we propose our genetic model and new genes for mobile and situated crowdsourcing systems by examining user contributions to the selected systems. We present the observed patterns of different genes and discuss how the model can be used to create new applications and design ideas. By reviewing the existing design principles of online communities, we also provide examples to illustrate how unique genes inspire new design suggestions for encouraging user contributions in the context of mobile and situated crowdsourcing. HighlightsA new perspective to survey mobile and situated crowdsourcing systems.A proposed genome containing 14 new genes that describe and categorize mobile and situated crowdsourcing systems.An extensive discussion on the observed patterns of the genes and how the unique mobile and situated crowdsourcing genes can be used to generate new application ideas and to inform new design suggestions for encouraging user contributions.
Year
DOI
Venue
2017
10.1016/j.ijhcs.2016.08.004
Int. J. Hum.-Comput. Stud.
Keywords
Field
DocType
Survey,Mobile crowdsourcing,Situated crowdsourcing,Genome,Design suggestions
Design elements and principles,Situated,Data science,Categorization,Crowdsourcing,Collective intelligence,Computer science,Knowledge management,Human–computer interaction
Journal
Volume
Issue
ISSN
102
C
1071-5819
Citations 
PageRank 
References 
2
0.44
46
Authors
3
Name
Order
Citations
PageRank
Yun Huang19212.01
Alain Shema251.51
Huichuan Xia3133.08