标题： 不透明性、模糊性和提问的几何学 显示英文标题

标题： Opacity, Obscurity, and the Geometry of Question-Asking

摘要： 提问是一种普遍的人类活动，但人们对是什么使得问题难以回答了解甚少。 对纽约时报填字游戏和问答节目《危险边缘》中的问题的两个大型数据库的分析，确立了问题难度的两个正交维度：晦涩性（答案的稀有性）和模糊性（问题提示的间接性，用word2vec进行操作化）。 模糊性的重要性以及协同信息在解决它中的作用表明，以先验期望来解释难度仅捕捉了提问过程的一部分。 进一步的回归分析显示了提问中存在其他维度：问题复杂性、答案的局部网络密度、提示交叉和信号词的存在。 我们的工作展示了提问者如何通过使用上下文提示来帮助他们的对话者，或者相反，如何对相关领域不熟悉会使个人从他人那里学习变得更加困难。 综合来看，这些结果表明，贝叶斯的问题难度模型可以通过过程模型以及个体用来导航概念空间的启发式方法来补充。 显示英文摘要

摘要： Asking questions is a pervasive human activity, but little is understood about what makes them difficult to answer. An analysis of a pair of large databases, of New York Times crosswords and questions from the quiz-show Jeopardy, establishes two orthogonal dimensions of question difficulty: obscurity (the rarity of the answer) and opacity (the indirectness of question cues, operationalized with word2vec). The importance of opacity, and the role of synergistic information in resolving it, suggests that accounts of difficulty in terms of prior expectations captures only a part of the question-asking process. A further regression analysis shows the presence of additional dimensions to question-asking: question complexity, the answer's local network density, cue intersection, and the presence of signal words. Our work shows how question-askers can help their interlocutors by using contextual cues, or, conversely, how a particular kind of unfamiliarity with the domain in question can make it harder for individuals to learn from others. Taken together, these results suggest how Bayesian models of question difficulty can be supplemented by process models and accounts of the heuristics individuals use to navigate conceptual spaces.