Abstract

In order to comprehensively evaluate the achievements of the 'Belt and Road' in integrated transportation, researchers need to optimize the method of generating evaluation indices and construct the framework structure of the 'Belt and Road' transportation index system. This paper used GDELT database as data source and obtained full text data of English news in 25 countries along ‘the Belt and Road’. The paper also introduced the topic model, combined with the unsupervised method (latent Dirichlet allocation, LDA) and the supervision method (labeled LDA) to mine the topics contained in the news data. It constructed the transportation development model and analyzed the development trend of transportation in various countries. The study found that the development trend of transportation in the countries along the line is unbalanced, which can be divided into four types: rapid development type, stable development type, slow development type and lagging development type. The method of this paper can effectively extract temporal and spatial variation of news events, discover potential risks in various countries, support real-time and dynamic monitoring of the social development situation of the countries along the border and provide auxiliary decision support for implementation of the ‘the Belt and Road’ initiative, which has important application value.

中文翻译：

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运输指数计算：一种基于开发主题的基于挖掘的方法

摘要

为了全面评价“一带一路”综合运输成果，研究人员需要优化评价指标的生成方法，构建“一带一路”运输指标体系的框架结构。本文以GDELT数据库为数据源，在“一带一路”沿线25个国家获得了英语新闻全文数据。本文还介绍了主题模型，并结合了无监督方法（潜在的Dirichlet分配，LDA）和监督方法（标记为LDA）来挖掘新闻数据中包含的主题。建立了交通运输发展模型，分析了各国交通运输的发展趋势。研究发现，沿线国家的交通发展趋势是不平衡的，可以分为快速发展型，稳定发展型，缓慢发展型和落后发展型四种。本文的方法可以有效地提取新闻事件的时空变化，发现各国的潜在风险，支持对沿线国家社会发展状况的实时动态监测，为实施突发事件提供辅助决策支持。 “一带一路”倡议具有重要的应用价值。