地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (11): 1956-1970.doi: 10.12082/dqxxkx.2021.210172

• 地球信息科学理论与方法 • 上一篇    下一篇

基于GDELT新闻数据的冲突强度定量表达及冲突事件检测研究

漆林(), 秦昆*(), 罗萍, 姚博睿, 朱炤瑗   

  1. 武汉大学遥感信息工程学院, 武汉 430079
  • 收稿日期:2021-04-02 修回日期:2021-05-17 出版日期:2021-11-25 发布日期:2022-01-25
  • 通讯作者: *秦昆(1972- ), 男,湖北随州人,博士,教授,研究方向为时空数据挖掘与大数据分析。E-mail: qink@whu.edu.cn
  • 作者简介:漆林(1997- ), 男,重庆江津人,硕士生,研究方向为时空数据挖掘。E-mail: qilin70@whu.edu.cn.
  • 基金资助:
    国家重点研发计划项目(2017YFB0503600);国家自然科学基金项目(U1833201)

Quantitative Expression of Conflict Intensity and Conflict Event Detection based on GDELT News Data

QI Lin(), QIN Kun*(), LUO Ping, YAO Borui, ZHU Zhaoyuan   

  1. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
  • Received:2021-04-02 Revised:2021-05-17 Online:2021-11-25 Published:2022-01-25
  • Supported by:
    National Key Research and Development Program, No(2017YFB0503600);National Natural Science Foundation of China, No(U1833201)

摘要:

全球范围内各种冲突经常发生,及时分析各种冲突关系并监测其变化,提前干预、实施人道主义救援,可以有效避免冲突的爆发与升级。冲突事件通常被各种新闻媒体及时报道,并被记录于新闻数据库中。提取新闻数据中的冲突事件信息并量化冲突强度,从而分析国家冲突强度的变化是一种可行思路。GDELT实时监测着不同来源的新闻,自动提取新闻中的事件与事件属性信息,并将事件总体划分为冲突与合作2种类型。本文以GDELT为数据源,综合考虑事件数量、事件影响性、事件关注度多个因素,针对不同空间研究尺度提出了一种利用全球冲突指数与局部冲突指数对冲突强度定量表达的方法。在全球尺度上,计算全球各国全球冲突指数衡量国家冲突强度,分析全球国家冲突强度空间分布规律。在国家尺度上,计算局部冲突指数衡量一个国家的冲突强度变化情况,并在冲突强度定量表达的基础上,研究一种基于距离的时间序列冲突检测方法检测冲突事件的发生。研究发现:① 冲突强度高的国家主要集中在非洲和中东地区,全球冲突强度在空间上存在明显的集聚现象;② 国家局部冲突指数的突增通常对应于一些冲突事件的发生,使用本文的冲突检测方法可以有效地及时检测这种突增现象,并能为冲突预警提供支持。本文的研究成果可以为国际冲突关系分析,以及国际救援组织的决策提供参考。

关键词: GDELT, 冲突强度, 全球冲突指数, 局部冲突指数, 冲突定量表达, 冲突检测, 空间分析

Abstract:

Conflicts occur frequently at any time and any place in the world. Conflicts often erupt between two or more parties. Analyzing the relation between various conflicts and monitoring the development and evolution of conflicts can help provide measures to intervene in conflicts and provide humanitarian assistance in the embryonic stage of conflicts, which can further help avoid the escalation of conflicts. Various conflict has attracted lots of attention from the public. The occurrence of various conflicts is usually reported by the news media in a timely manner, and each event information can be automatically collected by computers and recorded in news databases. The conflict news database contains a wealth of information. It provides a feasible way to extract the information of conflict events from the new data, quantify the conflict intensity, and analyze the change of national conflict intensity. The GDELT is such an excellent event database which monitors news from different sources around the world in real time, automatically extracts events and event attribute information in news, and classifies the event into conflict events and cooperation events. This paper uses GDELT event database as the data source and comprehensively obtains the number of events, the impact of the events, and the degree of attention to conflict events. We propose a method to quantitatively express the intensity of conflicts by using the global conflict index and the local conflict index for different spatial scales. At the global scale, we calculate the global conflict index of countries around the world to measure the intensity of national conflicts and analyze the spatial distribution of the intensity of global national conflicts. At the country level, the local conflict index is calculated to measure the change of conflict intensity in a country. Based on the quantitative expression of conflict intensity, a distance-based time series conflict detection method is employed to detect the occurrence of conflict events. The results show that: 1) Countries with high conflict intensity are mainly concentrated in Africa and the Middle East, and there is obvious spatial agglomeration of global conflict intensity; 2) The sudden increase in the national conflict index usually corresponds to the occurrence of some conflict events. The method of conflict detection in this paper can effectively detect the sudden increase in time and provide support for the early warning of conflicts. The research results of this paper can provide references for the analysis of international conflict relations and the decision-making of international rescue organizations.

Key words: GDELT, conflict intensity, global conflict index, local conflict index, conflict quantitative expression, conflict detection, spatial analysis