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Related Research on “The Belt and Road” Initiative Based on Big Data Text Mining: Taking the Domestic Area and the Korean Peninsula as an Example

DOI: 10.4236/oalib.1105742, PP. 1-15

Subject Areas: Statistics

Keywords: The Belt and Road, Text Clustering, TF-IDF, LDA Topic Model

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Abstract

As one of the core contents of China, “The Belt and Road” is very necessary to analyze the impact and significance of “The Belt and Road” on the domestic areas and Korean Peninsula areas in the context of big data. The text mining method was used to extract the core content and hot topics from the news reports of “The Belt and Road” in China and the Korean Peninsula in recent domestic and international news data. Using the unique attributes of public opinion media and news reports. Focusing on the key theme of “The Belt and Road”, using clustering algorithm and TF-IDF method, combined with LDA topic model, the structure and content of the theme are analyzed in detail on the pre-built big data analysis platform. The establishment of a big data platform and the use of TF-IDF and LDA topic models have improved the efficiency of data analysis. On the domestic front, the eastward extension of “The Belt and Road” is imperative and the prospects are clearer. On the Korean Peninsula, its own security situation is the core issue, and the United States is the biggest drag factor. In the future, it is necessary to focus on the common focus and solve the problem.

Cite this paper

Li, H. and Jin, Z. (2019). Related Research on “The Belt and Road” Initiative Based on Big Data Text Mining: Taking the Domestic Area and the Korean Peninsula as an Example. Open Access Library Journal, 6, e5742. doi: http://dx.doi.org/10.4236/oalib.1105742.

References

[1]  Hu, C., Lin, J. and Cui, Z. (2019) Research on the Regional Economic Development Situation Based on the “One Belt and Road” of Big Data. China Market, 11, 4-16.
[2]  Wang, L. (2018) The Path of Strengthening “One Belt and Road” to Foreign Cultural Communication. Youth Journalist, 10, 31-32.
[3]  Lv, Y. and Wang, H. (2018) Application of Big Data in Logistics Management in Belt and Road Initiative. Logistics Technology, 37, 25-28.
[4]  Noh, Y., Kim, T., Jeong, D.-K. and Lee, K.H. (2019) Trend Analysis of Convergence Research Based on Social Big Data. Journal of the Korea Contents Association, 19, 135-146.
[5]  Kim, M., Koo, C. and Sohn, B. (2019) A Study on the Effectiveness of Education Welfare Priority Support Program through Text Mining. Korean Journal of Youth Studies, 26, 313-332. https://doi.org/10.21509/KJYS.2019.02.26.2.313
[6]  Zhou, J., Xiong, Z. and Zhang, Y. (2006) Multi-Center Clustering Algorithm Based on Max-Min Distance Method. Journal of Computer Applications, 26, 1425-1427.
[7]  Wang, Y. and Tang, J. (2014) High-Efficiency K-Means Optimal Clustering Number Determination Algorithm. Journal of Computer Applications, 34, 1331-1335.
[8]  An, J., An, G. and Shi, Z. (2015) An Improved K-Means Text Clustering Algorithm. Transducer and Microsystem Technologies, 34, 130-133.
[9]  Dhillon, I.S. and Modha, D.S. (2001) Concept Decompositions for Large Sparse Text Data Using Clustering. Machine Learning, 42, 143-175.
https://doi.org/10.1023/A:1007612920971
[10]  Sun, J.G., Liu, J. and Zhao, L.Y. (2008) Clustering Algorithms Research. Journal of Software, 19, 48-61. https://doi.org/10.3724/SP.J.1001.2008.00048
[11]  Wang, C. and Zhang, J. (2014) Application of Improved K-Means Algorithm Based on LDA in Text Clustering. Journal of Computer Applications, 34, 249-254.
[12]  Blei, D.M., Ng, A.Y. and Jodan, M.I. (2003) Latent Dirichlet Allocation. Journal of Machine Learning Research, 3, 993-1022.
[13]  Steyvers, M. and Griffiths, T. (2007) Probabilistic Topic Models. In: Landauer, T.K., Mcnamara, D.S., Dennis, S. and Kinitsch, W., Eds., Latent Semantic Analysis: A Road to Meaning, Lawrence Erlbaum Associates Publishers, Mahwah, NJ.
[14]  Timothy, R.S. (2012) Deciphering North Korea’s Nuclear Rhetoric: An Automated Content Analysis of KCNA News. Asian Affairs: An American Review, 39, 73-89.
https://doi.org/10.1080/00927678.2012.678128

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