在Stack Overflow上的声誉是否总是用户专业知识的良好指标?不!

Shaowei Wang, D. Germán, T. Chen, Yuan Tian, Ahmed E. Hassan
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引用次数: 2

摘要

Stack Overflow (SO)用户是通过信誉点来识别的。声誉点通常是用户建立自己的职业生涯档案和展示他们在某些领域的专业知识的一个很好的途径。先前的研究使用用户的声誉作为代理来评估他们的经验和专业知识。然而,对于用户来说,有很多不需要太多专业知识就能获得声誉积分的方法,比如问一些高质量的问题。因此,理解高声誉点的含义以及声誉是否可以作为用户在Stack Overflow上的专业知识和经验的良好指标是很重要的。在这项研究中,我们探讨了用户如何通过挖掘他们的声誉相关活动(例如,提问、回答问题和编辑帖子)在Stack Overflow上获得声誉点。我们研究了93053个拥有至少1000个声誉点的高声誉用户的声誉相关活动。我们发现1)13.8%的被调查用户通过提问而不是回答问题获得了大部分声誉积分。2)一般来说,大多数发布的答案没有或很少获得声誉积分,用户从非常小比例的高投票答案中获得积分。12%的用户声誉来自于一个简单的回答。我们建议未来的研究和Stack Overflow引入一个新的度量(即vindex)来评估用户的专业知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Is reputation on Stack Overflow always a good indicator for users' expertise? No!
Stack Overflow (SO) users are recognized by reputation points. The reputation points are often a great avenue for users to build their career profile and demonstrate their expertise in some domains. Prior studies used users' reputation as a proxy to estimate their experience and expertise. However, there are various ways for a user to earn reputation points that do not require much expertise, such as asking high-quality questions. Therefore, it is important to understand the meaning of a high-reputation point and if the reputation could be used as a good indicator for users' expertise and experience on Stack Overflow. In this study, we explore how users earn reputation points on Stack Overflow by mining their reputation-related activities (e.g., asking questions, answering questions, and editing posts). We study the reputation-related activities of 93,053 high-reputation users that have at least 1,000 reputation points. We find that 1) 13.8% of the studied users earn their majority reputation points through asking questions rather than answering questions. 2) In general, most of the posted answers received no or very few reputation points with users gaining their points from a very small proportion of highly-voted answers. 12% of users' entire reputation comes from one single answer. We suggest future research and Stack Overflow introduce a new metric (i.e., vindex) to evaluate the expertise of a user.
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