Facultad de Ciencias, Universidad Nacional Autónoma de México, Ciudad de México, México.
Tecnológico Nacional de México, Tecnológico de Estudios Superiores de Ixtapaluca, Ixtapaluca, Estado de México, México.
PLoS One. 2022 Sep 15;17(9):e0274617. doi: 10.1371/journal.pone.0274617. eCollection 2022.
The study of natural language using a network approach has made it possible to characterize novel properties ranging from the level of individual words to phrases or sentences. A natural way to quantitatively evaluate similarities and differences between spoken and written language is by means of a multiplex network defined in terms of a similarity distance between words. Here, we use a multiplex representation of words based on orthographic or phonological similarity to evaluate their structure. We report that from the analysis of topological properties of networks, there are different levels of local and global similarity when comparing written vs. spoken structure across 12 natural languages from 4 language families. In particular, it is found that differences between the phonetic and written layers is markedly higher for French and English, while for the other languages analyzed, this separation is relatively smaller. We conclude that the multiplex approach allows us to explore additional properties of the interaction between spoken and written language.
使用网络方法研究自然语言已经使得我们能够从单个单词到短语或句子的层面来描述新的特性。定量评估口语和书面语之间相似性和差异性的一种自然方法是通过基于单词之间相似距离的多重网络来实现。在这里,我们使用基于拼写或语音相似性的单词多重表示来评估它们的结构。我们报告说,通过对网络拓扑性质的分析,在比较来自 4 个语系的 12 种自然语言的书面语和口语结构时,存在不同层次的局部和全局相似性。特别是,发现法语和英语的语音层和书面层之间的差异明显更高,而对于其他分析的语言,这种分离相对较小。我们得出结论,多重方法允许我们探索口语和书面语之间相互作用的其他特性。