PROGRESS IN GEOGRAPHY ›› 2019, Vol. 38 ›› Issue (7): 1009-1020.doi: 10.18306/dlkxjz.2019.07.006

• Special Column: the Belt and Road Initiative • Previous Articles     Next Articles

Big data analysis of social development situation in regions along the Belt and Road

Mingqing MA1,2(), Wu YUAN3, Quansheng GE1, Wen YUAN1,*(), Linsheng YANG1, Hanqing LI4, Meng LI1,2   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. University of the Chinese Academy of Sciences, Beijing 100049, China
    3. Computer School, Beijing Institute of Technology, Beijing 100081, China
    4. First Research Institute of the Ministry of Public Security of PRC, Beijing 100048, China
  • Received:2019-01-18 Revised:2019-05-15 Online:2019-07-28 Published:2019-07-28
  • Contact: Wen YUAN;
  • Supported by:
    Strategic Priority Research Program of the Chinese Academy of Sciences (Class A), No. XDA23100103;Key Project of the Chinese Academy of Sciences, No. ZDRW-ZS-2017-4.


The Belt and Road initiative has become China's basic international policy. Keeping abreast of the social development trend of countries along the Belt and Road is crucial to ensuring the steady progress and successful implementation of the initiative. To this end, this study used the Global Data on Events, Location and Tone (GDELT) as a data source to obtain the full-text English news data in 25 countries along the Belt and Road in the past five years, and analyzed the social development trends of various countries by introducing topic models and combining an unsupervised method—the latent Dirichlet allocation (LDA) and a supervised method—labeled latent Dirichlet allocation (Labeled LDA) to mine the topics contained in the news data, and construct a social stability model. The study found that: 1) The social development trend of the countries along the Belt and Road is uneven, and the countries can be divided into four categories: Stable, such as Oman, Vietnam; Relatively stable, such as Uzbekistan, Iran; Moderate risk, such as Kuwait, Jordan, Pakistan, Myanmar; High risk, such as Syria, Afghanistan. 2) Through the spatiotemporal mining of news topics, hot spots can be effectively identified. For example, this study found that Andijon has an important influence on the social development and stability of Central Asia. 3) The supervised topic model could reveal Uzbekistan's economic and industrial structure, identify major social events, and discover its social security risks and trend. This method can effectively explore the spatiotemporal changes of news events, discover potential risks of countries, support real-time dynamic monitoring of the social development trends of countries along the Belt and Road, and provide auxiliary decision support for the implementation of the Belt and Road initiative, and thus has important application value.

Key words: the Belt and Road Initiative, spatiotemporal data mining, theme modal, social situation, social stability, big data