著者

Kihei Magishi Tomoko Matsumoto Yutaka Shimada Tohru Ikeguchi

出版者

The Institute of Electronics, Information and Communication Engineers

雑誌

Nonlinear Theory and Its Applications, IEICE (ISSN:21854106)

巻号頁・発行日

vol.13, no.2, pp.343-348, 2022 (Released:2022-04-01)

参考文献数

22

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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.