论文标题
Argulens:使用论证模型对社区对可用性问题的看法解剖
ArguLens: Anatomy of Community Opinions On Usability Issues Using Argumentation Models
论文作者
论文摘要
在开源软件(OSS)中,可用性的设计通常会受到社区成员之间在诸如问题跟踪系统(ITS)等平台上的讨论的影响。但是,由于评论的数量和多样性,消化发行讨论中嵌入的丰富信息可能是一个重大挑战。我们提出和评估Argulens,这是一种概念框架和自动化技术,利用论证模型来支持对ITS中社区意见的有效理解和巩固。通过内容分析,我们对从一个大型的OSS项目中的高度讨论的可用性问题进行了解剖,将其论证组成部分和观点分解为。然后,我们尝试了监督的机器学习技术,以进行自动参数提取。最后,通过与经验丰富的用户的研究,我们证明了Argulens提供的信息支持了与可用性相关意见的消化,并促进了冗长问题的审查。 Argulens提供了设计有价值的工具的方向,用于高级推理和有关可用性的有效讨论。
In open-source software (OSS), the design of usability is often influenced by the discussions among community members on platforms such as issue tracking systems (ITSs). However, digesting the rich information embedded in issue discussions can be a major challenge due to the vast number and diversity of the comments. We propose and evaluate ArguLens, a conceptual framework and automated technique leveraging an argumentation model to support effective understanding and consolidation of community opinions in ITSs. Through content analysis, we anatomized highly discussed usability issues from a large, active OSS project, into their argumentation components and standpoints. We then experimented with supervised machine learning techniques for automated argument extraction. Finally, through a study with experienced ITS users, we show that the information provided by ArguLens supported the digestion of usability-related opinions and facilitated the review of lengthy issues. ArguLens provides the direction of designing valuable tools for high-level reasoning and effective discussion about usability.