Geek Talents: Who are the Top Experts on GitHub and Stack Overflow?
Geek Talents: Who are the Top Experts on GitHub and Stack Overflow?
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DOI：
10.32604/cmc.2019.07818
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发表时间：
2019-01-01
影响因子：
3.1
通讯作者：
McIntosh, Suzanne
中科院分区：
文献类型：
--
作者：
Tian, Yijun;Ng, Waii;McIntosh, Suzanne
在计算机科学领域，软件开发人员需要使用各种社交协作平台进行学习和合作。最受欢迎的是GitHub和堆栈溢出。现有平台仅支持搜索查询，以从GitHub提取相关的存储库信息，或者来自stack Overflow的问题和答案。这忽略了特定领域的顶级专家（怪胎才华），这忽略了有价值的编码人员相关的部分？这些信息对公司，开源项目以及想要从专家榜样学习的人来说很重要。因此，如何找到合适的开发人员是一个至关重要但充满挑战的问题。当前的大多数作品主要集中于推荐特定软件工程任务的专家，而忽略了不同项目中开发人员之间的关系。在本文中，我们提出了一种新颖的技术，该技术会自动识别Github，堆栈溢出以及两个社区的极客才能。结果表明，我们的工作在推荐不同领域的适当开发人员方面表现良好。
In the field of Computer Science, software developers need to use a wide array of social collaborative platforms for learning and cooperating. The most popular ones are GitHub and Stack Overflow. Existing platforms only support search queries to extract relevant repository information from GitHub, or questions and answers from Stack Overflow. This ignores the valuable coder-related part-who are the top experts (geek talents) in a specific area? This information is important to companies, open source projects, and to those who want to learn from an expert role model. Thus, how to find the right developers is quite a crucial yet challenging problem. Most of the current works mainly focus on recommending experts in a particular software engineering task and ignore the relationship between developers within different projects. In this paper, we propose a novel technique that automatically identifies geek talents from GitHub, Stack Overflow, and across both communities. The results show that our work performs well at recommending proper developers in diverse areas.