Discovering, Explaining and Summarizing Controversial Discussions in Community Q&A Sites
Developers often look for solutions to programming problems in community Q&A sites like Stack Overflow. Due to the crowdsourcing nature of these Q&A sites, many userprovided answers are wrong, less optimal or out-of-date. Relying on community-curated quality indicators (e.g., accepted answer, answer vote) cannot reliably identify these answer problems. Such problematic answers are often criticized by other users. However, these critiques are not readily discoverable when reading the posts. In this paper, we consider the answers being criticized and their critique posts as controversial discussions in community Q&A sites. To help developers notice such controversial discussions and make more informed choices of appropriate solutions, we design an automatic open information extraction approach for systematically discovering and summarizing the controversies in Stack Overflow and exploiting official API documentation to assist the understanding of the discovered controversies.We apply our approach to millions of java/androidtagged Stack overflow questions and answers and discover a large scale of controversial discussions in Stack Overflow. Our manual evaluation confirms that the extracted controversy information is of high accuracy. A user study with 18 developers demonstrates the usefulness of our generated controversy summaries in helping developers avoid the controversial answers and choose more appropriate solutions to programming questions.
Tue 12 NovDisplayed time zone: Tijuana, Baja California change
13:40 - 15:20 | Natural Language and Human AspectsResearch Papers / Demonstrations / Journal First Presentations at Cortez 2&3 Chair(s): Bogdan Vasilescu Carnegie Mellon University | ||
13:40 20mTalk | Discovering, Explaining and Summarizing Controversial Discussions in Community Q&A Sites Research Papers Xiaoxue Ren Zhejiang University, Zhenchang Xing Australia National University, Xin Xia Monash University, Guoqiang Li Shanghai Jiao Tong University, JianLing Sun Zhejiang University Pre-print | ||
14:00 20mTalk | Automating App Review Response Generation Research Papers Cuiyun Gao Nanyang Technological University, Singapore, Jichuan Zeng The Chinese University of Hong Kong, Xin Xia Monash University, David Lo Singapore Management University, Michael Lyu The Chinese University of Hong Kong, Irwin King The Chinese University of Hong Kong Pre-print | ||
14:20 20mTalk | Automatic Generation of Pull Request DescriptionsACM SIGSOFT Distinguished Paper Award Research Papers Zhongxin Liu Zhejiang University, Xin Xia Monash University, Christoph Treude The University of Adelaide, David Lo Singapore Management University, Shanping Li Zhejiang University Pre-print | ||
14:40 20mTalk | Recommending Who to Follow in the Software Engineering Twitter Space Journal First Presentations Abhishek Sharma Singapore Management University, Singapore, Yuan Tian Queens University, Kingston, Canada, Agus Sulistya School of Information Systems, Singapore Management University, Dinusha Wijedasa School of Information Systems, Singapore Management University, David Lo Singapore Management University Pre-print | ||
15:00 10mDemonstration | Developer Reputation Estimator (DRE) Demonstrations Sadika Amreen University of Tennessee Knoxville, Andrey Karnauch University of Tennessee Knoxville, Audris Mockus University of Tennessee - Knoxville | ||
15:10 10mDemonstration | CocoQa: Question Answering for Coding Conventions over Knowledge Graphs Demonstrations Tianjiao Du Shanghai JiaoTong University, Junming Cao Shanghai JiaoTong University, Qinyue Wu Shanghai JiaoTong University, Wei Li Shanghai JiaoTong University, Beijun Shen School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Yuting Chen Shanghai Jiao Tong University |