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首页> 外文会议>IEEE/ACM International Conference on Software Engineering >Journal First Understanding the Factors for Fast Answers in Technical QA Websites: An Empirical Study of Four Stack Exchange Websites
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Journal First Understanding the Factors for Fast Answers in Technical QA Websites: An Empirical Study of Four Stack Exchange Websites

机译：期刊第一了解技术问答网站的快速答案的因素：四个堆栈交换网站的实证研究

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摘要

Technical questions and answers (Q&A) websites accumulate a significant amount of knowledge from users. Developers are especially active on these Q&A websites, since developers are constantly facing new development challenges that require help from other experts. Over the years, Q&A website designers have derived several incentive systems (e.g., gamification) to encourage users to answer questions that are posted by others. However, the current incentive systems primarily focus on the quantity and quality of the answers instead of encouraging the rapid answering of questions. Improving the speed of getting an answer can significantly improve the user experience and increase user engagement on such Q&A websites. In this paper [1], we study the factors for fast answers on such Q&A websites. Our goal is to explore how one may improve the current incentive systems to motivate fast answering of questions. We use a logistic regression model to analyze 46 factors along four dimensions (i.e., question, asker, answer, and answerer dimension) in order to understand the relationship between the studied factors and the needed time to get an accepted answer. The question dimension calculates various textual and readability features of a question, as well as the popularity and difficulty of the question's tags. The asker dimension calculates the reputation of an asker and his/her historical tendency to get answers. The answer dimension computes textual features from the text of the accepted answer. The answerer dimension computes the historical activity level of the answerer who answered the question. We conduct our study on the four most popular (i.e., with the most questions) Q&A Stack Exchange websites: Stack Overflow, Mathematics, Ask Ubuntu, and Superuser. We find that i) factors in the answerer dimension have the strongest effect on the needed time to get an accepted answer, after controlling for other factors; ii) the current incentive system does not recognize non-frequent answerers who often answer questions which frequent answerers are not able to answer well. Such questions that are answered by non-frequent answerers are as important as those that are answered by frequent answerers; iii) the current incentive system motivates frequent answerers well, but such frequent answerers tend to answer short questions. Our findings suggest that the designers of Q&A website should improve their incentive systems to motivate non-frequent answerers to be more active and to answer questions faster, in order to shorten the waiting time for an answer (especially for questions that require specific knowledge that frequent answerers might not possess). In addition, the question answering incentive system needs to factor in the value and difficulty of answering the questions (e.g., by providing more rewards to harder questions or questions that remain unanswered for a long period of time).
机译：技术问题和答案（Q＆A）网站积累了来自用户的大量知识。开发人员对这些Q＆A网站特别活跃，因为开发人员不断面临新的发展挑战，需要其他专家的帮助。多年来，问答网站设计师派生了多个激励系统（例如，游戏化），以鼓励用户回答其他人发布的问题。然而，目前激励系统主要关注答案的数量和质量，而不是鼓励对问题的快速回答。提高获得答案的速度可以显着改善用户体验并提高用户在此类Q＆A网站上的用户参与。在本文[1]中，我们研究了关于此类Q＆A网站的快速答案的因素。我们的目标是探讨如何改善当前激励系统，激励问题的快速回答。我们使用Logistic回归模型来分析46个因素沿四个维度（即，问题，问员，答案和接听维度），以了解学习因素与所需时间之间的关系。问题尺寸计算问题的各种文本和可读性特征，以及问题标签的流行度和难度。问员维度计算了一位提问者的声誉和他/她的历史倾向来获得答案。答案维度从已接受答案的文本计算了文本功能。答案维度计算回答问题的历史活动水平。我们在四个最受欢迎的（即，最多的问题）Q＆A Stack Exchange网站上进行研究：堆栈溢出，数学，询问Ubuntu和超级用户。我们发现i）在控制其他因素后，应答者维度的因素对获得接受答案的所需时间最强烈的影响; ii）目前的激励制度不承认经常回答的非频繁的回答者，他们经常回答频繁接听者无法回答的问题。由非频繁回答者回答的这些问题与频繁的回答者回答的问题一样重要; iii）目前的激励系统很好地激励了频繁的回答者，但这种频繁的回答者倾向于回答简短的问题。我们的研究结果表明，问答网站的设计者应该改善他们的激励系统，激励不频繁的回答者更加活跃并更快地回答问题，以缩短答案的等待时间（特别是对于需要频繁的具体知识的问题回答者可能没有）。此外，应答激励系统的问题需要考虑回答问题的价值和难度（例如，通过为长时间仍未予以予以持续的问题或问题而提供更多奖励）。

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