因果好奇心的涌现：源自先验因果信念网络
The Emergence of Causal Curiosity from Prior Causal Belief Networks
AI总结：
本研究基于Reddit数据与语言模型，发现因果好奇心源于先验信念网络，偏好阳性名词和原因角色概念，并自网络中心涌现，可促进主动学习。
AI中文摘要：
因果好奇心是人类认知的基础。它是理解事件为何发生、其背后的机制是什么以及结果如何被解释或预期的渴望。它激发探索，维持注意力，并推动对新知识的寻求。然而，尽管对因果好奇心的重要性已有共识，关于因果好奇心如何从现有信念系统中产生，人们知之甚少。在我们的工作中，我们考察了因果好奇心如何从先验知识结构中涌现。利用2020年至2023年的Reddit数据，并借助语言模型提取因果关系对并识别由因果好奇心驱动的问题，我们的发现揭示出因果好奇心并非随机或独立的，而是很大程度上植根于先验知识结构。特别是，阳性名词更可能成为因果好奇心的对象。此外，我们的发现表明，更多作为原因的概念比更多作为结果的概念更可能出现在因果好奇心中。最后，我们的结果还表明，因果好奇心从先验信念网络的中心涌现。这些新颖的见解揭示出因果好奇心并非随机的，而是系统地基于先验知识结构，并表明它们通过激励人们主动探索和构建更深层次的理解而非被动接收信息，来促进人类学习过程的启示意义。
英文摘要：
Causal curiosity is foundational to human cognition. It is the desire to understand why events happen, what mechanisms underlie them, and how outcomes can be explained or anticipated. It motivates exploration, sustains attention, and fuels the search for new knowledge. However, despite consensus on the importance of causal curiosity, little is known about how causal curiosity arises from existing belief systems. In our work, we examine how causal curiosity emerges from prior knowledge structures. With Reddit data from 2020 to 2023, and leveraging language models to extract cause-and-effect relationship pairs and identify causal curiosity-driven questions, our findings reveal that causal curiosity is not random or independent, but largely rooted in prior knowledge structure. Particularly, \textit{positive} nouns are more likely to be the object of causal curiosity. Moreover, our findings indicate that concepts that serve more as \textit{causes} are more likely to appear in causal curiosity than those that serve more as effects. Lastly, our results also suggest that causal curiosity emerges from the \textit{central} of the prior belief network. These novel insights reveal that causal curiosity is not random but systematically grounded in prior knowledge structures, and suggest their implication to facilitate the human learning process by motivating people to actively explore and construct deeper understandings rather than passively receiving information.
