Canary: Extracting Requirements-Related Information from Online Discussions

Peter Sawyer, Georgi Kanchev, Amit Chopra, Pradeep Murukannaiah

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.
Original languageEnglish
Title of host publicationRequirements Engineering Conference (RE), 2017 IEEE 25th International
PublisherIEEE
DOIs
Publication statusPublished - 26 Sep 2017

Fingerprint

Query languages
Requirements engineering
Application programs
Semantics

Bibliographical note

© Copyright 2017 IEEE.

Keywords

  • Requirements elicitation; Crowdsourcing; Social media; Online discussions; Query language

Cite this

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 IEEE. https://doi.org/10.1109/RE.2017.83
Sawyer, Peter ; Kanchev, Georgi ; Chopra, Amit ; Murukannaiah, Pradeep. / Canary: Extracting Requirements-Related Information from Online Discussions. Requirements Engineering Conference (RE), 2017 IEEE 25th International. IEEE, 2017.
@inproceedings{6a368ba1282645e2a8f3d8e0f2601f10,
title = "Canary: Extracting Requirements-Related Information from Online Discussions",
abstract = "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.",
keywords = "Requirements elicitation; Crowdsourcing; Social media; Online discussions; Query language",
author = "Peter Sawyer and Georgi Kanchev and Amit Chopra and Pradeep Murukannaiah",
note = "{\circledC} Copyright 2017 IEEE.",
year = "2017",
month = "9",
day = "26",
doi = "10.1109/RE.2017.83",
language = "English",
booktitle = "Requirements Engineering Conference (RE), 2017 IEEE 25th International",
publisher = "IEEE",
address = "United States",

}

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. IEEE. https://doi.org/10.1109/RE.2017.83

Canary: Extracting Requirements-Related Information from Online Discussions. / Sawyer, Peter; Kanchev, Georgi ; Chopra, Amit; Murukannaiah, Pradeep.

Requirements Engineering Conference (RE), 2017 IEEE 25th International. IEEE, 2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Canary: Extracting Requirements-Related Information from Online Discussions

AU - Sawyer, Peter

AU - Kanchev, Georgi

AU - Chopra, Amit

AU - Murukannaiah, Pradeep

N1 - © Copyright 2017 IEEE.

PY - 2017/9/26

Y1 - 2017/9/26

N2 - 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.

AB - 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.

KW - Requirements elicitation; Crowdsourcing; Social media; Online discussions; Query language

U2 - 10.1109/RE.2017.83

DO - 10.1109/RE.2017.83

M3 - Conference contribution

BT - Requirements Engineering Conference (RE), 2017 IEEE 25th International

PB - IEEE

ER -

Sawyer P, Kanchev G, Chopra A, Murukannaiah P. Canary: Extracting Requirements-Related Information from Online Discussions. In Requirements Engineering Conference (RE), 2017 IEEE 25th International. IEEE. 2017 https://doi.org/10.1109/RE.2017.83