A study of innovation diffusion through link sharing on stack overflow

Yin

2015 IEEE Symposium on Service-Oriented System Engineering

et al. 2015

Collaborative development communities and knowledge sharing communities are highly correlated and mutually complementary. The knowledge sharing between these two types of open source communities can be very beneficial to both of them. However, it is a great challenge to automate this process. Current studies mainly focus on knowledge acquisition in one type of community, and few of them have tackle this problem efficiently. In this paper we take Android Issue Tracker and Stack Overflow as a case to study automatic knowledge sharing between them. We propose an automatic approach by integrating semantic similarity with temporal locality between Android issues and Stack Overflow posts to reveal the potential associations between them. Our approach exploits the rich semantics in finegrained information of issues and posts for associations building, and explores the temporal correlations between issues and posts in-depth for associations ranking. Extensive experiments show that the precision of our approach reaches 54.82% for top 10 recommendations when recommending Stack Overflow posts to Android issues, and 66.83% in reverse. This is significantly higher than the state-of-the-art method.

Section: Related Workmentioning

confidence: 99%

Automatic Knowledge Sharing Across Communities: A Case Study on Android Issue Tracker and Stack Overflow

Yin

2015 IEEE Symposium on Service-Oriented System Engineering

et al. 2015

“…These internal links, which connect related posts that focus on similar or related questions, form inter-connected knowledge graph [14]. In Android Issue Tracker we can see that there are also links refer to related issues.…”

Section: Citation-graph Based Clusteringmentioning

confidence: 99%

“…Their work proved the importance of effective knowledge management and sharing in software development. Gómez et al [14] focus on SO and studied the knowledge sharing in it. They found that SO plays an import role in software innovation dissemination.…”

Section: Related Workmentioning

confidence: 99%

Linking Issue Tracker with Q&A Sites for Knowledge Sharing across Communities

IEEE Trans. Serv. Comput.

Yin

et al. 2015

Collaborative development communities and knowledge sharing communities are highly correlated and mutually complementary. The knowledge sharing between these two types of open source communities can be very beneficial to both of them. However, it is a great challenge to automate this process. Current studies mainly focus on knowledge acquisition in one type of community, and few of them have tackle this problem efficiently. In this paper we take Android Issue Tracker and Stack Overflow as a case to study the mutual knowledge sharing between them. We propose an automatic approach by integrating semantic similarity with temporal locality between Android issues and Stack Overflow posts based on the internal citation-graph to reveal the potential associations between them. Our approach explores the internal citations in communities for closely related posts or issues clustering, exploits the rich semantics in fine-grained information of issues and posts for associations building, and leverages the temporal correlations between issues and posts in-depth for associations ranking. Extensive experiments show that the precision of our approach reaches 62.51% for top 10 recommendations when recommending Stack Overflow posts to Android issues, and 66.83% in reverse.

Proceedings of the 23rd International Conference on World Wide Web

“…Therefore, Stack Overflow has attracted increasing attention from different research communities like software engineering, human computer interaction, social computing and data mining [6,9,10,21,22]. Researchers have mined the Stack Overflow knowledge-base to extract interesting and unique insights like API usage obstacles, innovation diffusion via URL link sharing,mobile development issues and programming topic trends [9,13,18,25]. Questions on Stack Overflow have received focused attention from researchers.…”

Section: Related Workmentioning

confidence: 99%

Chaff from the wheat

Correa

Sureka

2014

Stack Overflow is the most popular Community based Question Answering (CQA) website for programmers on the web with 2.05M users, 5.1M questions and 9.4M answers. Stack Overflow has explicit, detailed guidelines on how to post questions and an ebullient moderation community. Despite these precise communications and safeguards, questions posted on Stack Overflow can be extremely off topic or very poor in quality. Such questions can be deleted from Stack Overflow at the discretion of experienced community members and moderators. We present the first study of deleted questions on Stack Overflow. We divide our study into two parts -(i) Characterization of deleted questions over ≈ 5 years (2008-2013) of data, (ii) Prediction of deletion at the time of question creation.Our characterization study reveals multiple insights on question deletion phenomena. We find that it takes substantial time to vote a question to be deleted but once voted, the community takes swift action. We also see that question authors delete their questions to salvage reputation points. We notice some instances of accidental deletion of good quality questions but such questions are voted back to be undeleted quickly. We discover a pyramidal structure of question quality on Stack Overflow and find that deleted questions lie at the bottom (lowest quality) of the pyramid. We also build a predictive model to detect the deletion of question at the creation time. We experiment with 47 features -based on User Profile, Community Generated, Question Content and Syntactic style -and report an accuracy of 66%. Our findings reveal important suggestions for content quality maintenance on community based question answering websites. To the best of our knowledge, this is the first large scale study on poor quality (deleted ) questions on Stack Overflow.