Using human evaluation of 100,000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language, observing that (1) the words of natural human language possess a universal positivity bias; (2) the estimated emotional content of words is consistent between languages under translation; and (3) this positivity bias is strongly independent of frequency of word usage. Alongside these general regularities, we describe inter-language variations in the emotional spectrum of languages which allow us to rank corpora. We also show how our word evaluations can be used to construct physical-like instruments for both real-time and offline measurement of the emotional content of large-scale texts.

通过对来自10种语言、24个语料库的100,000个单词的人类评估结果，我们发现自然人类语言中存在一种普遍存在的积极偏差，并且这种偏好与词频强烈独立；通过描述语言的情感谱，我们可以比较不同语料库的差异，并利用词汇评估构建情感内容实时和离线测量工具。

人类语言呈现出普遍的积极偏向性