Title
Studying Social Collaboration Features and Patterns in Service Crowdsourcing.
Abstract
Service crowdsourcing follows typical social collaboration processes with stochastic and dynamic characteristics. In this paper, the "bug-fix" social collaboration on GitHub is used as a case scenario of crowdsourcing, and 53,475 issues in 10 OSS projects are collected to conduct an empirical study on features and patterns of service crowdsourcing. Seven collaboration features (CFs) are proposed to delineate social characteristics of crowdsourcing. In terms of these CFs, social collaboration processes are clustered and results show that these features have significant distinguishability. An extended Generalized Sequential Pattern (GSP) algorithm is put forward to identify two types of collaboration patterns called participant-oriented pattern (PP) and role-oriented pattern (RP), and the richness and individualized degree of collaboration patterns in different OSS projects are analyzed and compared.
Year
DOI
Venue
2016
10.1007/978-3-319-46295-0_49
Lecture Notes in Computer Science
Keywords
Field
DocType
Service crowdsourcing,Social collaboration process,Collaboration pattern,Collaboration features,Open Source Software(OSS)
Data science,Computer science,Crowdsourcing,Knowledge management,Social collaboration,Empirical research
Conference
Volume
ISSN
Citations 
9936
0302-9743
0
PageRank 
References 
Authors
0.34
9
4
Name
Order
Citations
PageRank
Hao Yu122.10
Zhong-Jie Wang235664.60
Xu Chi300.68
Xiaofei Xu440870.26