A Visual Analysis of the Hotspots of the National Security and Language Studies in the Context of Big Data
Year: 2024
Type: conference-paper
Abstract: This paper explores the convergence of national security and language, a critical but under-explored area of contemporary scholarship. It adopts a visual analytical approach, using bibliometric techniques and CiteSpace software to analyse 2,039 journal articles from the Web of Science Core Collection. All of these articles have been published over the past 38 years (1986-2024) on the topic of national security and language. The aim of this paper is to map knowledge using big data mining, to identify research hotspots in the field of language and national security, and to visualize the results using knowledge mapping software. The analysis focuses on publication time, keyword co-occurrence, citation bursts and their clustering relationships. The findings reveal that: (1)there has been a significant rise in academic interest in the field of language and national security since 1986, with a notable increase after 2014, which underscores the growing awareness of the critical role of language in national security discourse and practice; (2) the research hotspots of national security and language research are divided into nine main clusters, namely, #0 food security, #1 European Union, #2politics, #3 discourse analysis, #4 national language processing, #5 security, #6 national security, #7 national identity and #8 globalization. Future research should aim to further explore the intersection of language and national security by incorporating a wider range of sources, including non-English literature, in order to enrich the understanding of this field and to examine the potential impact of emerging technologies such as artificial intelligence and machine learning on the dynamics of language in the security contexts.
Authors: Xiaoqing Yang, Xiaobo Liang
Institution: National University of Defense Technology
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W4410210828