research-article

CoArgue : Fostering Lurkers’ Contribution to Collective Arguments in Community-based QA Platforms

Authors:

Chengzhong Liu,

Xiaojuan MaAuthors Info & Claims

CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

Article No.: 271, Pages 1 - 17

https://doi.org/10.1145/3544548.3580932

Published: 19 April 2023 Publication History

Abstract

In Community-Based Question Answering (CQA) platforms, people can participate in discussions about non-factoid topics by marking their stances, providing premises, or arguing for the opinions they support, which forms “collective arguments”. The sustainable development of collective arguments relies on a big contributor base, yet most of the frequent CQA users are lurkers who seldom speak out. With a formative study, we identified detailed obstacles preventing lurkers from contributing to collective arguments. We consequently designed a processing pipeline for extracting and summarizing augmentative elements from question threads. Based on this we built CoArgue, a tool with navigation and chatbot features to support CQA lurkers’ motivation and ability in making contributions. Through a within-subject study (N=24), we found that, compared to a Quora-like baseline, participants perceived CoArgue as significantly more useful in enhancing their motivation and ability to join collective arguments and found the experience to be more engaging and productive.

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Cited By

He CDeng YHe LGuo QZhang YLu ZLi B(2024)Engage Wider Audience or Facilitate Quality Answers? a Mixed-methods Analysis of Questioning Strategies for Research Sensemaking on a Community Q&A SiteProceedings of the ACM on Human-Computer Interaction10.1145/36373278:CSCW1(1-31)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637327

Index Terms

CoArgue : Fostering Lurkers’ Contribution to Collective Arguments in Community-based QA Platforms
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Empirical studies in HCI
    2. Interactive systems and tools

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CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

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DOI:10.1145/3544548

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He CDeng YHe LGuo QZhang YLu ZLi B(2024)Engage Wider Audience or Facilitate Quality Answers? a Mixed-methods Analysis of Questioning Strategies for Research Sensemaking on a Community Q&A SiteProceedings of the ACM on Human-Computer Interaction10.1145/36373278:CSCW1(1-31)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3637327

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