Classification of natural language messages using a coordination game
提出一种协调博弈游戏来对自然语言消息进行分类，并与自我分类和标准内容分析比较，发现该游戏因参与者获得显著奖励而具有优势。
Abstract The role of natural language communication in economic exchange has been the focus of substantial experimental analysis. Recently, scholars have taken the important step of investigating whether certain types of communication (e.g., promises) might affect decisions differently than other types of communication. This requires classifying natural language messages. Unfortunately, no broadly-accepted method is available for this purpose. We here describe a coordination game for classification of natural language messages. The game is similar in spirit to the “ESP” game that has proven successful for the classification of tens of millions of internet images. We compare our approach to self-classification as well as to classifications based on a standard content analysis. We argue that our classification game has advantages over those alternative approaches, and that these advantages might stem from the salient rewards earned by our game's participants.