TITLE:
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
AUTHORS:
Hongyi Li, Zhezhi Jin
KEYWORDS:
The Belt and Road, Text Clustering, TF-IDF, LDA Topic Model
JOURNAL NAME:
Open Access Library Journal,
Vol.6 No.9,
September
16,
2019
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.