What makes Question & Answer (Q&A) communities productive? In this paper, we look into how the diversity of behavioral types of agents impacts the performance of Q&A communities using different performance metrics. We do this by developing an agent-based model informed by insights from previous studies on Q&A communities. By analyzing the different strategies for how questions are selected to answer, we find that there are mixtures of strategies leading to the best outcomes for different performance conditions. Particularly, Q&A communities that encourage participants to focus on answering the new questions reach the best performance in answering the questions, creating the long term value, and improving the competence of solving difficulty. In conclusion, we find that the current strategies of question selection on Stack Overflow are in line with the high performance of producing public benefit from the collective attention available.

中文翻译：

---

用户行为如何影响在线问答社区的成功

是什么让问答 (Q&A) 社区富有成效？在本文中，我们研究了代理行为类型的多样性如何使用不同的绩效指标影响问答社区的绩效。我们通过开发一个基于代理的模型来实现这一点，该模型基于以前对问答社区的研究的见解。通过分析如何选择问题来回答的不同策略，我们发现存在多种策略的混合，从而在不同的性能条件下产生最佳结果。特别是鼓励参与者专注于回答新问题的问答社区在回答问题、创造长期价值和提高解决困难的能力方面表现最佳。综上所述，