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GDELT数据网络化挖掘与国际关系分析
Networked Mining of GDELT and International Relations Analysis

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秦昆 *   罗萍   姚博睿  
文摘 21世纪以来的国际关系错综复杂、瞬息万变,给世界的经济、安全、外交等带来了深刻变化。这些变化对中国的内外政策产生了重大影响。全面及时地分析国际关系及其变化特征,对于中国的经济和外交发展规划具有重要参考价值。国际关系研究具有复杂性、及时性、时空性等特点,迫切需要时空大数据分析技术为其提供新的思路和技术手段。大众媒体如报纸、广播等记录着世界上发生的各种各样的事件,蕴含着丰富的信息,相对于记录个人活动的社交媒体数据,其更加适合于对人类社会进行大规模和长时间的分析。GDELT是一个免费开放的新闻数据库,它实时监测世界上印刷、广播、网络媒体中的新闻,对其进行文本分析并提取出人物、地点、组织和事件等关键信息。本文利用复杂网络的理论和方法对GDELT进行网络化挖掘并进一步分析国家关系。首先利用该数据构建国家交互网络,然后通过网络特征统计分析国家之间的交互关系,最后探测国家冲突事件交互网络的时序变化。研究发现:①国家交互网络具有无标度特性,网络连接在整体和局部上都呈现出不均匀性,少数国家与其他国家有大量交互,大多数国家与其他国家的交互很少;一个国家与少数国家有大量交互,而与大多数国家的交互很少。②国家冲突事件交互网络的突然变化往往对应一些重大事件。本文的研究可以为大数据时代的国际关系探索提供一个新的视角,同时也为新闻媒体数据的分析提供参考。
其他语种文摘 The international relations are intricate and ever-changing since the 21st century,and have brought profound changes to the world's economy,security,and diplomacy.These changes have had a major impact on China's internal and external policies.A comprehensive and timely analysis of international relations and its changing characteristics has important reference value for China's economic and diplomatic development planning.The analysis of international relations has spatio-temporal characteristics,and it needs real-time processing.Thus,it needs to introduce the methods of spatio-temporal big data analysis to analyze international relations.Traditional mass media such as news,radio,etc.record all kinds of events happening in the world.It contains a wealth of information.Compared with social media data recording personal activities,it is more suitable for large-scale and long-term analysis of human society.The Global Database of Events Language,and Tone (GDELT) is a free and open news database which monitors news from print,broadcast,and online media in the world,analyzes the texts and extracts the key information such as people,place,organization,and event.This paper researches the network characteristics of GDELT based on theory of complex network and further analyze the relations between countries.Firstly,this paper constructs national interaction networks using GDELT,then analyze the interaction relationship between countries through network characteristic statistics,and finally detect the time series changes of the national conflict event interaction network.The results show that:(1)The National interaction network has scale-free characteristics,the interaction between countries is unevenly distributed from a global and local perspective.Very few countries have lots of interactions while most countries have very few interactions,and one country has lots of interactions with a few countries while a few interactions with most countries.(2) Sudden changes in the national interaction network of conflict events often indicates some significant national conflict events.This paper can provide a new perspective for the exploration of international relations and a reference for the analysis of news media in the era of big data.
来源 地球信息科学学报 ,2019,21(1):14-24 【核心库】
DOI 10.12082/dqxxkx.2019.180674
关键词 GDELT ; 空间交互网络 ; 时空大数据分析 ; 国际关系 ; 复杂网络 ; 无标度分布
地址

武汉大学遥感信息工程学院, 武汉, 430079

语种 中文
文献类型 研究性论文
ISSN 1560-8999
学科 自动化技术、计算机技术
基金 国家重点研发计划项目 ;  国家自然科学基金项目
文献收藏号 CSCD:6415536

参考文献 共 37 共2页

1.  Lazer D. Computational social science. Science,2014,323(1):721-723 被引 2    
2.  Kang C. Understanding operation behaviors of taxicabs in cities by matrix factorization. Computers Environment & Urban Systems,2016,60:79-88 被引 7    
3.  Eagle N. Inferring friendship network structure by using mobile phone data. Proceeding the National Academy of Sciences of the United States of America,2009,106(36):15274-15278 被引 65    
4.  Mazzitello K I. Effects of mass media and cultural drift in a model for social influence. International Journal of Modern Physics C,2007,18(9):1475-1482 被引 1    
5.  . The GDELT Project,2018 被引 1    
6.  Leetaru K. Gdelt:Global data on events, location, and tone, 1979-2012. ISA annual convention,2013,2(4):1-49 被引 3    
7.  Kwak H. A first look at global news coverage of disasters by using the gdelt dataset. International Conference on Social Informatics,2014:300-308 被引 2    
8.  Su Y. Tracking public response and relief efforts following the 2015 Nepal earthquake. IEEE, International Conference on Collaboration and Internet Computing,2016:495-499 被引 1    
9.  Degtyarev D. Interconnections among the United States, Russia and China:Does Kissinger's American leadership formula apply?. International Organizations Research Journal,2017,12(1):81-109 被引 1    
10.  方鹏. 基于Django的海量媒体数据分析平台的设计与实现,2017 被引 3    
11.  Bi S. A contrast of the degree of activity among the three major powers, USA, China, and Russia:Insights from media reports. International Conference on Behavioral, Economic and Socio-Cultural Computing,2015:38-42 被引 1    
12.  Sagi D J B. Using GDELT data to evaluate the confidence on the Spanish government energy policy. International Journal of Interactive Multimedia and Artificial Intelligence,2016,3(6):38-43 被引 3    
13.  龚为纲. 社会情绪的结构性分布特征及其逻辑-基于互联网大数据GDELT的分析. 政治学研究,2018(4):90-102 被引 3    
14.  Alikhani E. Computational social analysis:Social unrest prediction using textual analysis of news,2014 被引 1    
15.  Yonamine J E. Predicting future levels of violence in Afghanistan districts using gdelt,2018 被引 1    
16.  Qiao F. Predicting social unrest events with hidden markov models using GDELT. Discrete Dynamics in Nature and Society,2017,2017:1-13 被引 2    
17.  Keneshloo Y. Detecting and forecasting domestic political crises:A graph-based approach. ACM Conference,2014:192-196 被引 2    
18.  Qiao F. Computational approach to detecting and predicting occupy protest events. International Conference on Identification, Information, and Knowledge in the Internet of Things,2015:94-97 被引 1    
19.  Elshendy M. Big data analysis of economic news:Hints to forecast macroeconomic indicators. International Journal of Engineering Business Management,2017,9:1-12 被引 3    
20.  Phua C. Visual and predictive analytics on Singapore news:Experiments on GDELT. Wikipedia, andSTI 被引 1    
引证文献 18

1 刘毅 粤港澳大湾区区域一体化及其互动关系 地理学报,2019,74(12):2455-2466
被引 31

2 秦昆 空间综合人文学与社会科学研究综述 地球信息科学学报,2020,22(5):912-928
被引 10

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