The structure and dynamics of knowledge network in domain-specific Q&A sites: a case study of stack overflow
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- 作者：Deheng Ye ; Zhenchang Xing ; Nachiket Kapre
- 关键词：Mining software repositories ; Crowdsourced knowledge ; Domain ; specific Q&A ; URL sharing ; Network analysis ; Human factors
- 刊名：Empirical Software Engineering
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：22
- 期：1
- 页码：375-406
- 全文大小：
- 刊物类别：Computer Science
- 刊物主题：Software Engineering/Programming and Operating Systems; Programming Languages, Compilers, Interpreters;
- 出版者：Springer US
- ISSN：1573-7616
- 卷排序：22
文摘
Programming-specific Q&A sites (e.g., Stack Overflow) are being used extensively by software developers for knowledge sharing and acquisition. Due to the cross-reference of questions and answers (note that users also reference URLs external to the Q&A site. In this paper, URL sharing refers to internal URLs within the Q&A site, unless otherwise stated), knowledge is diffused in the Q&A site, forming a large knowledge network. In Stack Overflow, why do developers share URLs? How is the community feedback to the knowledge being shared? What are the unique topological and semantic properties of the resulting knowledge network in Stack Overflow? Has this knowledge network become stable? If so, how does it reach to stability? Answering these questions can help the software engineering community better understand the knowledge diffusion process in programming-specific Q&A sites like Stack Overflow, thereby enabling more effective knowledge sharing, knowledge use, and knowledge representation and search in the community. Previous work has focused on analyzing user activities in Q&A sites or mining the textual content of these sites. In this article, we present a methodology to analyze URL sharing activities in Stack Overflow. We use open coding method to analyze why users share URLs in Stack Overflow, and develop a set of quantitative analysis methods to study the structural and dynamic properties of the emergent knowledge network in Stack Overflow. We also identify system designs, community norms, and social behavior theories that help explain our empirical findings. Through this study, we obtain an in-depth understanding of the knowledge diffusion process in Stack Overflow and expose the implications of URL sharing behavior for Q&A site design, developers who use crowdsourced knowledge in Stack Overflow, and future research on knowledge representation and search.