What is it about?
Stack Overflow provides valuable support to computer science practitioners, it often contains low quality content that impacts users’ contributions and their longevity. Most low-quality content comes from ignoring netiquette rules and community norms during discussions between the question setter and the answerer. Researchers have raised the challenge of how to address these violations using technical solutions. However, previous work has not reviewed the scale of scientific attention that is given to this cause. Therefore in this study, we fill this research gap using a Systematic Mapping Study approach. We used five relevant databases, reviewed 1,489 papers and selected 18 that are relevant to help to address this gap.
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Why is it important?
This study represents a shortcoming in terms of the research community understanding the focus of academic studies when considering Community Question Answering platforms and how research is conducted on these forums. We have found that research interest to improve content quality of Stack Overflow is increasing. However, the majority of the research was conducted using manual qualitative and quantitative analysis approaches. Therefore, further research is required to spot violation features Community Question Answering platforms using computational analysis such as machine learning methods.
Perspectives
The journey from conceptualization to publication of our paper on content quality in community question answering platforms using a systematic mapping study has been an intellectually stimulating and gratifying experience. We meticulously navigated through existing research, uncovering insights that shed light on the complex dynamics of online knowledge exchange. Engaging with the research community provided valuable perspectives, refining our understanding and approach. With our paper now published, we feel a sense of accomplishment, knowing it contributes to the ongoing discourse on online community dynamics. Moving forward, we eagerly anticipate how our findings will shape future research and the evolution of community question answering platforms, recognizing the continual exploration and discovery ahead.
Mrs Gheida Shahrour
Keele University
Read the Original
This page is a summary of: The Content Quality of Crowdsourced Knowledge on Stack Overflow- A Systematic Mapping Study, November 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3625007.3627729.
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