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Sparrows and Owls: Characterisation of Expert Behaviour in StackOverflow

机译:麻雀和猫头鹰:StackOverflow中专家行为的表征

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Question Answering platforms are becoming an important repository of crowd-generated knowledge. In these systems a relatively small subset of users is responsible for the majority of the contributions, and ultimately, for the success of the Q/A system itself. However, due to built-in incentivization mechanisms, standard expert identification methods often misclassify very active users for knowledgable ones, and misjudge activeness for expertise. This paper contributes a novel metric for expert identification, which provides a better characterisation of users' expertise by focusing on the quality of their contributions. We identify two classes of relevant users, namely sparrows and owls, and we describe several behavioural properties in the context of the StackOverflow Q/A system. Our results contribute new insights to the study of expert behaviour in Q/A platforms, that are relevant to a variety of contexts and applications.
机译:问答平台正在成为人群产生的知识的重要存储库。在这些系统中,相对较小的用户子集负责大部分贡献,并最终负责Q / A系统本身的成功。但是,由于内置的​​激励机制,标准的专家识别方法经常将非常活跃的用户分类为知识渊博的用户,而对专家的活跃度进行了错误的判断。本文为专家鉴定提供了一种新颖的指标,通过关注用户的贡献质量来更好地表征用户的专业知识。我们确定了两类相关的用户,即麻雀和猫头鹰,并在StackOverflow Q / A系统的上下文中描述了几种行为属性。我们的结果为研究Q / A平台中的专家行为提供了新的见解,这些见解与各种上下文和应用程序有关。

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