New research approaches empowered by big data spur research innovation in international and regional studies.  Photo: TUCHONG

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Big data is a product of the development of internet technology, typically characterized by the “5V” attributes: volume, velocity, variety, value, and validity. With its extensive sample sizes and multidimensional variables, big data integrates both the scale and depth needed for comprehensive analysis. Research and application in this field, therefore, require innovative approaches, such as social network analysis, data visualization analysis, and spatial data analysis. These methods differ from traditional research techniques, offering new avenues for changes and development in international and regional studies. 

Classification  

The data used for research on various countries and organizations worldwide constitutes a vast amount of big data, which can be broadly classified into two types.

The first type is static data, often encompassing traditional databases. The transition of academic research into the digital era introduced a primary shift in data resources: the digitization of paper-based materials. Initially, this meant converting books, journals, and other materials into digital images through scanning, though these image-based resources were generally not searchable. The next stage was digital text conversion, where text recognition was applied to scanned materials, enabling content searches and greatly improving data usage efficiency. Once systematically organized, these raw resources form databases. The commercial and open-source databases commonly found on the market today are of this type and are known as “version 1.0 databases.” 

In the context of international and regional studies, the largest static database currently in operation is the “Countries, Regions and Global Governance Data Platform” (CRGG) developed by Social Sciences Academic Press (China). The precursor to this platform is the “Guide to the World States” series and the electronic resources developed based on it, which integrate comprehensive information, primary data, and research findings in the fields of countries, regions, and international organizations. In addition to comprehensive database resources, some domestic universities and research institutions have also developed specialized databases, such as the American Studies Information System (ASIS) developed by  Fudan University, which aims to build a public service platform for American studies and provide in-depth information for professional researchers while also serving as a window for the general public to learn about the United States. 

Globally, one of the largest foreign-language databases for international and regional studies is provided by Gale Data Publishing Group, a reference materials publisher under the US company Cengage Learning. Gale offers hundreds of online databases, among which are the National Geographic Virtual Library of the United States and the Smithsonian Institution’s American History (primary sources).  

The second type of big data is the dynamic data platform, also known as “version 2.0 databases.” This type builds upon traditional static data sources and incorporates dynamic tracking of websites, media, information, forums, and other open-source channels, spanning countries and regions of interest. Using data mining techniques, these platforms collect data in real time, on scheduled intervals, or at high frequencies for key areas. This constant updating and data storage allows researchers to stay up-to-date with the latest developments in the regions they study, which is essential for international and regional studies. 

Currently, the most representative dynamic data platform is the “China-ASEAN Big Data” platform developed by Guangxi University. The platform aligns with the goals of the China-ASEAN Information Harbor, integrating resources from the government, universities, research institutions, and enterprises. Leveraging cloud computing, the Internet of Things, and big data technologies, it provides comprehensive, multi-faceted insights into the political, economic, military, educational, and cultural dimensions of ASEAN countries. With capabilities for real-time public opinion tracking, the platform offers rigorously curated data, assisting government policy-making and supporting corporate investment decisions with high-quality intelligence. 

In addition, the Ministry of Education is also building similar digital platforms for international and regional studies. The development and utilization of these new platforms are expected to elevate the overall quality of China’s research in this field. 

Approaches

The widespread use of big data offers valuable support for high-quality international and regional studies. Given the unique characteristics of big data compared to traditional datasets, its use and analysis requires updated methodologies. 

First, social network analysis plays a big role. An important aspect of international and regional studies is analyzing important political figures in various countries, and social network analysis provides a valuable approach by examining these individuals’ social networks. This method studies interpersonal relationships and social networks primarily by using data visualization tools to create network maps that represent the connections between individuals, organizations, and society. Following the advent of the internet, social media users generate massive amounts of data—including users’ locations, content, and timestamps—that can be analyzed to assess specific events across geographic areas or social platforms. Through social network analysis, it is possible to reveal the ways in which organizations and individuals interact, the pathways of information dissemination, and influence within networks, thereby providing a better understanding of human relationships. This provides an important channel for character analysis in international and regional studies. 

Second, text data analysis is essential due to the extensive textual material involved in international and regional studies. Big data-based text analysis automates the mining and examination of large-scale textual information. Using statistical analysis software, text analysis includes data collection, segmentation, cleaning, feature extraction, and modeling. Outputs can be visualized and analyzed through word clouds, sentiment analysis, clustering, social network analysis and other methods, helping researchers to better interpret and understand text data and information and thus deepen their understanding of international and regional issues. 

Third, big data visualization is crucial for international and regional studies, which often involve huge datasets. Big data visualization transforms complex datasets into accessible visual formats, such as charts, graphs, and maps, making the data more intuitive, easier to understand, and more useful for analysis. This approach enables researchers to leverage big data more effectively to support decision-making and judgment. 

In addition to these three commonly used big data techniques, geographic information systems (GIS) and other specialized applications also play significant roles in international and regional studies, enabling targeted research and generating valuable results in specialized fields. 

Examples

The emergence and application of big data have not only expanded the objects of international and regional studies from national and systemic levels to the individual level, but also extended the scope of research from the macro to the micro level. In the era of big data, researchers can access extensive information not only from static databases but also from various software tools that rapidly mine individual data from the internet, broadening the scope and depth of research. 

Case 1: The Belt and Road Institute at Hainan University follows  social media accounts of influential individuals and uses machine learning models to analyze their postings and those of their followers. This analysis provides a preliminary assessment of the mutual influence between public figures and their followers. 

Case 2: The Visualization and Visual Analysis Laboratory at Peking University analyzes the personal conduct of prominent foreign state leaders by visualizing tweets. Social media platforms, which some leaders often use for sharing and communication, offer a substantial amount of content suitable for building a textual data set that can be observed and studied. Mining this textual data allows researchers to roughly construct behavioral profiles based on their online activities. 

Case 3: The international relations research team at Tsinghua University uses “event data analysis” to analyze inter-state relations. In international and regional studies, the bilateral relationship between two countries is a common research theme. Traditionally, researchers relied on historical and political research methods to provide qualitative descriptions of bilateral relations. With big data, Tsinghua’s team has transitioned to a quantitative approach, cataloging and organizing diplomatic events between China and major countries such as the United States, Japan, Russia, the United Kingdom, France, and Germany since 1950. By quantifying bilateral relations, compiling databases, and visualizing changes in these bilateral relationships on a coordinate graph, they enable researchers to gain a more detailed understanding of the changes in the relationship between China and foreign countries and make more accurate predictions about their future development. 

Innovation is the driving force behind the continuous progress of international and regional studies. With the increasing application of big data in international and regional studies, the construction of various databases will continue to improve, and the important role of big data-based research methods will become increasingly prominent. 

Chen Guangmeng is a professor from the Academy of International and Regional Studies at Sichuan International Studies University.

Edited by ZHAO YUAN