Online discussions about software applications generate a large amount of requirements-related information. This information can potentially be usefully applied in requirements engineering; however currently, there are few systematic approaches for extracting such information. To address this gap, we propose Canary, an approach for extracting and querying requirements-related information in online discussions. The highlight of our approach is a high-level query language that combines aspects of both requirements and discussion in online forums. We give the semantics of the query language in terms of relational databases and SQL. We demonstrate the usefulness of the language using examples on real data extracted from online discussions. Our approach relies on human annotations of online discussions. We highlight the subtleties involved in interpreting the content in online discussions and the assumptions and choices we made to effectively address them. We demonstrate the feasibility of generating high-quality annotations by obtaining them from lay Amazon Mechanical Turk users.
|Title of host publication||Requirements Engineering Conference (RE), 2017 IEEE 25th International|
|Publication status||Published - 26 Sep 2017|
|Name||2017 IEEE 25th International Requirements Engineering Conference (RE)|
Bibliographical note© Copyright 2017 IEEE.
- Requirements elicitation; Crowdsourcing; Social media; Online discussions; Query language
Sawyer, P., Kanchev, G., Chopra, A., & Murukannaiah, P. (2017). Canary: Extracting Requirements-Related Information from Online Discussions. In Requirements Engineering Conference (RE), 2017 IEEE 25th International (2017 IEEE 25th International Requirements Engineering Conference (RE)). IEEE. https://doi.org/10.1109/RE.2017.83