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Geek Talents: Who are the Top Experts on GitHub and Stack Overflow?

Yijun Tian 1, *, Waii Ng1, Jialiang Cao1, Suzanne McIntosh1

1 New York University, Courant Institute of Mathematical Sciences, New York, 10012, USA.

* Corresponding Author: Yijun Tian. Email: email.

Computers, Materials & Continua 2019, 61(2), 465-479. https://doi.org/10.32604/cmc.2019.07818

Abstract

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.

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Cite This Article

APA Style
, Y.T., Ng, W., Cao, J., McIntosh, S. (2019). Geek talents: who are the top experts on github and stack overflow?. Computers, Materials & Continua, 61(2), 465-479. https://doi.org/10.32604/cmc.2019.07818
Vancouver Style
YT, Ng W, Cao J, McIntosh S. Geek talents: who are the top experts on github and stack overflow?. Comput Mater Contin. 2019;61(2):465-479 https://doi.org/10.32604/cmc.2019.07818
IEEE Style
Y.T. , W. Ng, J. Cao, and S. McIntosh "Geek Talents: Who are the Top Experts on GitHub and Stack Overflow?," Comput. Mater. Contin., vol. 61, no. 2, pp. 465-479. 2019. https://doi.org/10.32604/cmc.2019.07818

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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