Mining requirements arguments from user forums

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

Abstract

In order to sustain, software systems have to evolve in favor of its main target users. Due to the pervasive adoption of online user forums and social media, collecting users feedbacks and comments become possible. However, such crowd generated data are often fragmented, with various viewpoints mentioned during a series of message exchange. The aim of the thesis is to propose an argumentation-based CrowdRE approach, which represents such group conversations as a user argumentation model with the original conversation structure reserved. Based on the argumentation model, we are able to identify new features proposed by the crowd-users or issues encountered, and their supporting and attacking arguments using argumentation theory. To accomplish this research, we adopted an abstract argumentation, bipolar argumentation framework, and coalition-based meta argumentation framework. In addition, to provided automated support to our proposed approach, algorithms will be developed for bipolar argumentation, coalition-based meta argumentation, and end-users voting mechanism. Finally, this thesis employees different machine learning algorithms to automatically classify crowd-users comments into rationale elements and identify conflict-free features or claims based on their supporting and attacking arguments. Initial results show that the proposed approach can identify features, issues and their supporting and attacking arguments with acceptable performance.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 27th International Requirements Engineering Conference, RE 2019
EditorsDaniela Damian, Anna Perini, Seok-Won Lee
PublisherIEEE Computer Society
Pages440-445
Number of pages6
ISBN (Electronic)9781728139128
DOIs
Publication statusPublished - Sept 2019
Externally publishedYes
Event27th IEEE International Requirements Engineering Conference, RE 2019 - Jeju Island, Korea, Republic of
Duration: 23 Sept 201927 Sept 2019

Publication series

NameProceedings of the IEEE International Conference on Requirements Engineering
Volume2019-September
ISSN (Print)1090-705X
ISSN (Electronic)2332-6441

Conference

Conference27th IEEE International Requirements Engineering Conference, RE 2019
Country/TerritoryKorea, Republic of
CityJeju Island
Period23/09/1927/09/19

Keywords

  • Argumentation
  • Machine learning
  • Natural language processing
  • Requirements
  • User forum

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