It is often stated that human languages, as other biological systems, are shaped by cost-cutting pressures but, to what extent? Attempts to quantify the degree of optimality of languages by means of an optimality score have been scarce and focused mostly on English. Here we recast the problem of the optimality of the word order of a sentence as an optimization problem on a spatial network where the vertices are words, arcs indicate syntactic dependencies and the space is defined by the linear order of the words in the sentence. We introduce a new score to quantify the cognitive pressure to reduce the distance between linked words in a sentence. The analysis of sentences from 93 languages representing 19 linguistic families reveals that half of languages are optimized to a 70% or more. The score indicates that distances are not significantly reduced in a few languages and confirms two theoretical predictions, i.e. that longer sentences are more optimized and that distances are more likely to be longer than expected by chance in short sentences. We present a new hierarchical ranking of languages by their degree of optimization. The new score has implications for various fields of language research (dependency linguistics, typology, historical linguistics, clinical linguistics and cognitive science). Finally, the principles behind the design of the score have implications for network science.
翻译:通常有人说,人类语言与其他生物系统一样,受成本削减压力的影响,但程度如何?试图通过优化评分来量化语言的最佳程度,但这种尝试很少,而且主要侧重于英语。在这里,我们重新将句子的单词顺序优化问题作为空间网络的一个优化问题,在空间网络中,句子是单词,弧线表示综合依赖性,用句子的线性顺序界定空间。我们引入新的评分,量化认知压力,以减少句子中关联词的距离。对代表19种语言家庭的93种语言的评分分析显示,半数语言被优化到70%或以上。评分表明,少数语言的距离没有显著缩短,并证实了两种理论预测,即句子更优化,短句子的距离更有可能超过预期的时间。我们根据语言的优化程度对语言进行新的等级排序。新评分对语言研究的不同领域产生了影响(依赖语言学、语言学、历史学、临床学分对最后的排序影响)。