An empirical study on developer interactions in StackOverflow
Shaowei Wang,David Lo,Lingxiao Jiang +2 more
- pp 1019-1024
TLDR
Latent Dirichlet Allocation (LDA), a well known topic modeling approach, is used to analyze the contents of tens of thousands of questions and answers, and LDA provides an alternative perspective different from that of Treude et al. for categorizing StackOverflow questions.Abstract:
StackOverflow provides a popular platform where developers post and answer questions. Recently, Treude et al. manually label 385 questions in StackOverflow and group them into 10 categories based on their contents. They also analyze how tags are used in StackOverflow. In this study, we extend their work to obtain a deeper understanding on how developers interact with one another on such a question and answer web site. First, we analyze the distributions of developers who ask and answer questions. We also investigate if there is a segregation of the StackOverflow community into questioners and answerers. We also perform automated text mining to find the various kinds of topics asked by developers. We use Latent Dirichlet Allocation (LDA), a well known topic modeling approach, to analyze the contents of tens of thousands of questions and answers, and produce five topics. Our topic modeling strategy provides an alternative perspective different from that of Treude et al. for categorizing StackOverflow questions. Each question can now be categorized into several topics with different probabilities, and the learned topic model could automatically assign a new question to several categories with varying probabilities. Last but not least, we show the distributions of questions and developers belonging to various topics generated by LDA.read more
Citations
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How do API changes trigger stack overflow discussions? a study on the Android SDK
TL;DR: It is suggested that Android developers usually have more questions when the behavior of APIs is modified, and deleting public methods from APIs is a trigger for questions that are more discussed and of major interest for the community, and posted by more experienced developers.
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Mining duplicate questions in stack overflow
TL;DR: A manual investigation is performed to understand why users submit duplicate questions in Stack Overflow and a classification technique is proposed that uses a number of carefully chosen features to identify duplicate questions with reasonable accuracy.
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SOTorrent: reconstructing and analyzing the evolution of stack overflow posts
TL;DR: SOTorrent as discussed by the authors provides access to the version history of Stack Overflow content at the level of whole posts and individual text or code blocks by aggregating URLs from text blocks and collecting references from GitHub files to SO posts.
References
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