Nonlinear Theory and Its Applications, IEICE
Online ISSN : 2185-4106
ISSN-L : 2185-4106
Special Section on Nonlinear Science Workshop on the Journal
Investigation of the structural features of word co-occurrence networks with increasing numbers of connected words
Kihei MagishiTomoko MatsumotoYutaka ShimadaTohru Ikeguchi
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2022 Volume 13 Issue 2 Pages 343-348


Word co-occurrence networks (WCNs) are a major tool used to analyze languages quantitatively. In a WCN, the vertices are words (morphemes), and the edges connect n consecutive words in a sentence on the basis of the n-gram. Most studies use WCNs transformed at n=2. In this study, we investigated the changes in the structural features of WCNs when n increases using four types of documents for eight languages. We found that WCNs with n≧ 3 reflect features of the languages that do not appear when n = 2 and that some structural features evaluated by network measures depend on the text data.

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