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  1. Proceedings of the 1st International Workshop on Crowd-based Software Development Methods and Technologies (CrowdSoft 2014)
  2. Exploring the patterns of social behavior in GitHub
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How the crowd impacts commercial applications: a user-oriented approach
Recommending relevant projects via user behaviour: an exploratory study on github
SmartHR: a resume query and management system based on semantic web
Crowdsourcing in the Brazilian IT industry: what we know and what we don't know
Exploring the patterns of social behavior in GitHub
Personalized mobile application discovery
Using clustering and transitivity to reduce the costs of crowdsourced entity resolution
Investigating social media in GitHub's pull-requests: a case study on Ruby on Rails
A novel multilayered context awareness technology for internetware evolution
iTest: testing software with mobile crowdsourcing
Estimating the dynamic performance of composed services: a probability theory based approach

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Conference Proceedings

Exploring the patterns of social behavior in GitHub

Content Provider ACM Digital Library
Author Wang, Huaimin Wang, Tao Yu, Yue Yin, Gang
Abstract Social coding paradigm is reshaping the distributed software development with a surprising speed in recent years. Github, a remarkable social coding community, attracts a huge number of developers in a short time. Various kinds of social networks are formed based on social activities among developers. Why this new paradigm can achieve such a great success in attracting external developers, and how they are connected in such a massive community, are interesting questions for revealing power of social coding paradigm. In this paper, we firstly compare the growth curves of project and user in GitHub with three traditional open source software communities to explore differences of their growth modes. We find an explosive growth of the users in GitHub and introduce the Diffusion of Innovation theory to illustrate intrinsic sociological basis of this phenomenon. Secondly, we construct follow-networks according to the follow behaviors among developers in GitHub. Finally, we present four typical social behavior patterns by mining follow-networks containing independence-pattern, group-pattern, star-pattern and hub-pattern. This study can provide several instructions of crowd collaboration to newcomers. According to the typical behavior patterns, the community manager could design corresponding assistive tools for developers. .
Starting Page 31
Ending Page 36
Page Count 6
File Format PDF
ISBN 9781450332248
DOI 10.1145/2666539.2666571
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2014-11-17
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Distributed software development Behavior pattern Social network Social coding
Content Type Text
Resource Type Article
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