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首页> 外文期刊>Psychological science: a journal of the American Psychological Society >Longitudinal Analysis of Early Semantic Networks:Preferential Attachment or Preferential Acquisition?
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Longitudinal Analysis of Early Semantic Networks:Preferential Attachment or Preferential Acquisition?

机译：早期语义网络的纵向分析：优先依附还是优先获取？

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摘要

Analyses of adult semantic networks suggest a learning mechanism involving preferential attachment: A word is more likely to enter the lexicon the more connected the known words to which it is related. We introduce and test two alternative growth principles: preferential acquisition_words enter the lexicon not because they are related to well-connected words, but because they connect well to other words in the learning environment_and the lure of the associates_new words are favored in proportion to their connections with known words. We tested these alternative principles using longitudinal analyses of developing networks of 130 nouns children learn prior to the age of 30 months. We tested both networks with links between words represented by features and networks with links represented by associations. The feature networks did not predict age of acquisition using any growth model. The associative networks grew by preferential acquisition, with the best model incorporating word frequency, number of phonological neighbors, and connectedness of the new word to words in the learning environment, as opera_tionalized by connectedness to words typically acquired by the age of 30 months.
机译：对成人语义网络的分析提出了一种涉及优先依恋的学习机制：一个单词越有可能进入词典，与该单词相关的已知单词之间的联系越紧密。我们介绍并测试了两种替代的增长原理：优先习得词进入词典不是因为它们与联系良好的单词相关，而是因为它们与学习环境中的其他单词具有良好的联系—以及同事的诱惑力—新单词与其联系成比例地受到青睐用已知的单词。我们通过对30个年龄在30个月以下的儿童学习的名词发展网络的纵向分析，对这些替代原则进行了测试。我们测试了两个具有特征表示的单词之间的链接的网络以及具有关联所表示的链接的网络。特征网络无法使用任何增长模型来预测采集的年龄。联想网络是通过优先获取而增长的，最好的模型结合了单词频率，语音邻域数量以及学习环境中新单词与单词的连接性，如通过与通常在30个月时获得的单词的连接性进行操作。

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