Abstract
On 22 March 2018, the United States and China started a trade war which sparked a heated discussion about its impact on global economy and trade. This paper uses web crawler to collect Weibo blogs about this trade war, extracts the main content of these blogs with natural language processing methods and tools, clusters similar blogs by K-Means algorithm, analyzes the topics in these blogs and provides a reference for predicting the future of this trade war.
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Acknowledgment
The work of Su Hu was jointly supported by the MOST Program of International S&T Cooperation (Grant No. 2016YFE0123200), National Natural Science Foundation of China (Grant No.61471100/61571082/61701503), and Science and Technology on Electronic Information Control Laboratory (Grant No. 6142105040103). The author would also like to thank all the reviewers, their suggestions help improve the work a lot.
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Cheng, S., Gao, Y., Li, X., Hu, S. (2020). An Analysis on the Weibo Topic “US-China Trade War” Based on K-Means Algorithm. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1037. Springer, Cham. https://doi.org/10.1007/978-3-030-29516-5_30
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DOI: https://doi.org/10.1007/978-3-030-29516-5_30
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