Siew Cynthia S Q, Vitevitch Michael S
Department of Psychology, National University of Singapore, Singapore 117570, Singapore.
Department of Psychology, University of Kansas, Lawrence, KS 66045, USA.
Entropy (Basel). 2020 Sep 15;22(9):1029. doi: 10.3390/e22091029.
Recent work investigating the development of the phonological lexicon, where edges between words represent phonological similarity, have suggested that phonological network growth may be partly driven by a process that favors the acquisition of new words that are phonologically similar to several existing words in the lexicon. To explore this growth mechanism, we conducted a simulation study to examine the properties of networks grown by inverse preferential attachment, where new nodes added to the network tend to connect to existing nodes with fewer edges. Specifically, we analyzed the network structure and degree distributions of artificial networks generated via either preferential attachment, an inverse variant of preferential attachment, or combinations of both network growth mechanisms. The simulations showed that network growth initially driven by preferential attachment followed by inverse preferential attachment led to densely-connected network structures (i.e., smaller diameters and average shortest path lengths), as well as degree distributions that could be characterized by non-power law distributions, analogous to the features of real-world phonological networks. These results provide converging evidence that inverse preferential attachment may play a role in the development of the phonological lexicon and reflect processing costs associated with a mature lexicon structure.
最近有关语音词汇发展的研究工作表明，单词之间的边代表语音相似性，语音网络的增长可能部分由一个过程驱动，该过程有利于获取与词汇表中几个现有单词在语音上相似的新单词。为了探索这种增长机制，我们进行了一项模拟研究，以检验通过反向优先连接生长的网络的特性，在这种情况下，添加到网络的新节点倾向于连接到边较少的现有节点。具体来说，我们分析了通过优先连接、优先连接的反向变体或两种网络生长机制的组合生成的人工网络的网络结构和度分布。模拟结果表明，最初由优先连接驱动、随后由反向优先连接驱动的网络生长导致了密集连接的网络结构（即直径更小和平均最短路径长度更小），以及可以用非幂律分布表征的度分布，这类似于真实世界语音网络的特征。这些结果提供了一致的证据，表明反向优先连接可能在语音词汇的发展中起作用，并反映了与成熟词汇结构相关的处理成本。
