We study games with natural‐language labels (i.e., strategic problems where options are denoted by words), for which we propose and test a measurable characterization of prominence. We assume that—ceteris paribus—players find particularly prominent those strategies that are denoted by words more frequently used in their everyday language. To operationalize this assumption, we suggest that the prominence of a strategy‐label is correlated with its frequency of occurrence in large text corpora, such as the Google Books corpus (“n‐gram” frequency). In testing for the strategic use of word frequency, we consider experimental games with different incentive structures (such as incentives to and not to coordinate), as well as subjects from different cultural/linguistic backgrounds. Our data show that frequently‐mentioned labels are more (less) likely to be selected when there are incentives to match (mismatch) others. Furthermore, varying one's knowledge of the others' country of residence significantly affects one's reliance on word frequency. Overall, the data show that individuals play strategies that fulfill our characterization of prominence in a (boundedly) rational manner.

中文翻译：

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带有自然语言标签的游戏​​的突出概念

我们研究带有自然语言标签的游戏​​（即，用单词表示选项的战略问题），为此我们提出并测试了突出的可测量特征。我们假设-塞特里（Certeris paribus）-玩家发现那些以日常语言中更常用的单词表示的策略尤其突出。为了使这一假设可行，我们建议策略标签的突出程度与其在大型文本语料库中的出现频率相关，例如Google Books语料库（“ n-gram”频率）。在测试单词频率的策略使用时，我们考虑了具有不同激励结构（例如对和不对协调），以及来自不同文化/语言背景的主题。我们的数据表明，当有动机与其他人匹配（不匹配）时，经常选择的标签被选择的可能性就更高（更少）。此外，改变一个人对他人居住国的了解会极大地影响一个人对单词频率的依赖。总体而言，数据显示，个人所玩的策略以（有限的）理性方式满足了我们对突出性的刻画。