Prosociality (measured with economic games) is correlated with individual differences in psychological constructs (measured with self-report scales). We review how methods from natural language processing, a subfield of computer science focused on processing natural text, can be applied to understand the semantic content of scales measuring psychological constructs correlated with prosociality. Methods for clustering language and assessing similarity between text documents can be used to assess the novelty (or redundancy) of new scales, to understand the overlap among different psychological constructs, and to compare different measures of the same construct. These examples illustrate how natural language processing methods can augment traditional survey- and game-based approaches to studying individual differences in prosociality.

亲社会性（用经济游戏衡量）与心理结构的个体差异（用自我报告量表衡量）相关。我们回顾了自然语言处理（专注于处理自然文本的计算机科学的一个子领域）的方法如何应用于理解测量与亲社会性相关的心理结构的量表的语义内容。聚类语言和评估文本文档之间相似性的方法可用于评估新量表的新颖性（或冗余性），了解不同心理结构之间的重叠，以及比较同一结构的不同度量。这些例子说明了自然语言处理方法如何增强传统的基于调查和游戏的方法来研究亲社会性的个体差异。