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An empirical study of Chinese language networks

Author

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  • Zhou, Shuigeng
  • Hu, Guobiao
  • Zhang, Zhongzhi
  • Guan, Jihong

Abstract

Chinese is spoken by the largest number of people in the world, and it is regarded as one of the most important languages. In this paper, we explore the statistical properties of Chinese language networks (CLNs) within the framework of complex network theory. Based on one of the largest Chinese corpora, i.e. People’s Daily Corpus, we construct two networks (CLN1 and CLN2) from two different respects, with Chinese words as nodes. In CLN1, a link between two nodes exists if they appear next to each other in at least one sentence; in CLN2, a link represents that two nodes appear simultaneously in a sentence. We show that both networks exhibit small-world effect, scale-free structure, hierarchical organization and disassortative mixing. These results indicate that in many topological aspects Chinese language shapes complex networks with organizing principles similar to other previously studied language systems, which shows that different languages may have some common characteristics in their evolution processes. We believe that our research may shed some new light into the Chinese language and find some potentially significant implications.

Suggested Citation

  • Zhou, Shuigeng & Hu, Guobiao & Zhang, Zhongzhi & Guan, Jihong, 2008. "An empirical study of Chinese language networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(12), pages 3039-3047.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:12:p:3039-3047
    DOI: 10.1016/j.physa.2008.01.024
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    Citations

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    Cited by:

    1. Li, Jianyu & Zhou, Jie & Luo, Xiaoyue & Yang, Zhanxin, 2012. "Chinese lexical networks: The structure, function and formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(21), pages 5254-5263.
    2. Liang, Wei & Shi, Yuming & Huang, Qiuling, 2014. "Modeling the Chinese language as an evolving network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 268-276.
    3. Liang, Wei & Wang, Yanli & Shi, Yuming & Chen, Guanrong, 2015. "Co-occurrence network analysis of modern Chinese poems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 284-293.
    4. Liang, Wei & Shi, Yuming & Tse, Chi K. & Liu, Jing & Wang, Yanli & Cui, Xunqiang, 2009. "Comparison of co-occurrence networks of the Chinese and English languages," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(23), pages 4901-4909.
    5. Sheng, Long & Li, Chunguang, 2009. "English and Chinese languages as weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(12), pages 2561-2570.
    6. Huang, Wei & Yang, Kailin & Ma, Jiming & Xu, Yaowu & Guo, Xinlei & Wang, Jue, 2018. "A new setting criterion of tailrace surge chambers for pumped-storage power plants," Renewable Energy, Elsevier, vol. 116(PA), pages 194-201.
    7. Wang, Junjie & Zhou, Shuigeng & Guan, Jihong, 2011. "Characteristics of real futures trading networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 398-409.
    8. Yang, Yi & Song, Yue, 2023. "Resistance-distance betweenness: Definition, properties, and application in complex linguistic networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    9. Junjie Wang & Shuigeng Zhou & Jihong Guan, 2010. "Characteristics of Real Futures Trading Networks," Papers 1004.4402, arXiv.org, revised Feb 2011.
    10. Liang, Wei & Chen, Guanrong, 2016. "Spectral analysis of Chinese language: Co-occurrence networks from four literary genres," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 49-56.
    11. Ghosh, Dipak & Chakraborty, Sayantan & Samanta, Shukla, 2019. "Study of translational effect in Tagore’s Gitanjali using Chaos based Multifractal analysis technique," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1343-1354.

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