BurstBiRank: Co-Ranking Developers and Projects in GitHub with Complex Network Structures and Bursty Interactions
With the wide adoption of social collaborative coding, more and more developers participate and collaborate on platforms such as GitHub through rich social and technical relationships, forming a large-scale complex technical system. Like the functionalities of critical nodes in other complex systems...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/7264396 |
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| _version_ | 1832550087984676864 |
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| author | Dengcheng Yan Zhen Shao Yiwen Zhang Bin Qi |
| author_facet | Dengcheng Yan Zhen Shao Yiwen Zhang Bin Qi |
| author_sort | Dengcheng Yan |
| collection | DOAJ |
| description | With the wide adoption of social collaborative coding, more and more developers participate and collaborate on platforms such as GitHub through rich social and technical relationships, forming a large-scale complex technical system. Like the functionalities of critical nodes in other complex systems, influential developers and projects usually play an important role in driving this technical system to more optimized states with higher efficiency for software development, which makes it a meaningful research direction on identifying influential developers and projects in social collaborative coding platforms. However, traditional ranking methods seldom take into account the continuous interactions and the driving forces of human dynamics. In this paper, we combine the bursty interactions and the bipartite network structure between developers and projects and propose the BurstBiRank model. Firstly, the burstiness between each pair of developers and projects is calculated. Secondly, a weighted developer-project bipartite network is constructed using the burstiness as weight. Finally, an iterative score diffusion process is applied to this bipartite network and a final ranking score is obtained at the stationary state. The real-world case study on GitHub demonstrates the effectiveness of our proposed BurstBiRank and the outperformance of traditional ranking methods. |
| format | Article |
| id | doaj-art-948b82d81fca445d9754b694f48e78c6 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-948b82d81fca445d9754b694f48e78c62025-02-03T06:07:41ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/72643967264396BurstBiRank: Co-Ranking Developers and Projects in GitHub with Complex Network Structures and Bursty InteractionsDengcheng Yan0Zhen Shao1Yiwen Zhang2Bin Qi3Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, ChinaSchool of Computer Science and Technology, Anhui University, Hefei 230601, ChinaSchool of Computer Science and Technology, Anhui University, Hefei 230601, ChinaSchool of Computer Science and Technology, Anhui University, Hefei 230601, ChinaWith the wide adoption of social collaborative coding, more and more developers participate and collaborate on platforms such as GitHub through rich social and technical relationships, forming a large-scale complex technical system. Like the functionalities of critical nodes in other complex systems, influential developers and projects usually play an important role in driving this technical system to more optimized states with higher efficiency for software development, which makes it a meaningful research direction on identifying influential developers and projects in social collaborative coding platforms. However, traditional ranking methods seldom take into account the continuous interactions and the driving forces of human dynamics. In this paper, we combine the bursty interactions and the bipartite network structure between developers and projects and propose the BurstBiRank model. Firstly, the burstiness between each pair of developers and projects is calculated. Secondly, a weighted developer-project bipartite network is constructed using the burstiness as weight. Finally, an iterative score diffusion process is applied to this bipartite network and a final ranking score is obtained at the stationary state. The real-world case study on GitHub demonstrates the effectiveness of our proposed BurstBiRank and the outperformance of traditional ranking methods.http://dx.doi.org/10.1155/2020/7264396 |
| spellingShingle | Dengcheng Yan Zhen Shao Yiwen Zhang Bin Qi BurstBiRank: Co-Ranking Developers and Projects in GitHub with Complex Network Structures and Bursty Interactions Complexity |
| title | BurstBiRank: Co-Ranking Developers and Projects in GitHub with Complex Network Structures and Bursty Interactions |
| title_full | BurstBiRank: Co-Ranking Developers and Projects in GitHub with Complex Network Structures and Bursty Interactions |
| title_fullStr | BurstBiRank: Co-Ranking Developers and Projects in GitHub with Complex Network Structures and Bursty Interactions |
| title_full_unstemmed | BurstBiRank: Co-Ranking Developers and Projects in GitHub with Complex Network Structures and Bursty Interactions |
| title_short | BurstBiRank: Co-Ranking Developers and Projects in GitHub with Complex Network Structures and Bursty Interactions |
| title_sort | burstbirank co ranking developers and projects in github with complex network structures and bursty interactions |
| url | http://dx.doi.org/10.1155/2020/7264396 |
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