Παγκόσμιες τάσεις Έρευνας εφαρμογών της Τεχνητής Νοημοσύνης στην Εθνική και Διεθνή Πολιτική: μια Βιβλιομετρική Ανάλυση

Published: Jan 2, 2026
Versions:
2026-01-02 (1)
Keywords:
Artificial Intelligence, National Politics International Politics Authorship Multiple Correspondence Analysis Hierarchical Clustering
LABORATORY TEACHING PERSONNEL
a:1:{s:5:"el_GR";s:45:"ΠΑΝΕΠΙΣΤΗΜΙΟ ΜΑΚΕΔΟΝΙΑΣ";}
PROFESSOR
UNIVERSITY OF MACEDONIA
Abstract

The applications of AI in national and international politics, as well as in international relations, are growing. Geostrategic alliances are being challenged, new challenges are being introduced to the international agenda, and diplomats and negotiators have useful tools at their disposal to carry out their work. At the same time, new issues related to human rights are being raised. Artificial intelligence algorithms can directly analyse changing conditions during international crises, allowing the parties involved to act promptly and decisively. Machine learning algorithms are able to monitor social media, international news sources and other data streams in order to effectively circulate content while being able to identify early indicators of impending conflicts or humanitarian emergencies. 


Using R language tools, this study takes a bibliometric approach to the digital literature of the discipline of AI in national and international policy in order to create a survey of the field. To capture this image, relevant metadata such as annual production rates, most relevant sources, global citation frequencies, collaboration indices, affiliation frequency distributions, relevant word frequencies and word network dynamics are highlighted and analyzed. The datasets are further subjected to analysis through the Multiple Correspondence Analysis (MCA) method combined with Hierarchical Clustering (HC). The aim of this multivariate statistical analysis is to discern patterns and correlations between the digital authorship metrics of the specific subject matter and, through this process, the semantic understanding of AI engagement in national and international policy.

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Author Biographies
LABORATORY TEACHING PERSONNEL, a:1:{s:5:"el_GR";s:45:"ΠΑΝΕΠΙΣΤΗΜΙΟ ΜΑΚΕΔΟΝΙΑΣ";}

Dimitrios Vagianos is a graduate of the School of Electrical and Computer Engineering of the Aristotle University of Thessaloniki. He holds a Master of Science degree with distinction in Mobile Communication Systems from the University of Surrey, UK, and a PhD degree from the Department of International and European Studies of the University of Macedonia in the field of Big Data Mining and Analysis of the Social Web. He is a member of the Laboratory Teaching Personnel at the University of Macedonia where he teaches in Greek and English independent undergraduate and postgraduate courses. His scientific work has been published as peer-reviewed articles in various scientific journals and as chapters in edited volumes of international publishers. [More details at www.uom.gr/en/vagianos]

PROFESSOR, UNIVERSITY OF MACEDONIA

Nikolaos Koutsoupias is a professor at the Department of International and European Studies, where he teaches courses in Computer Science and Data Analysis. His research interests include qualitative data analysis, text mining, social network analysis, art data analysis, and epistemology. He has published numerous scientific articles in international journals, book volumes, and conference proceedings. He is the head of the Governance and Information and Communication Technology Lab (GICT-Lab) and Director of the MSc in European Youth Policies, Entrepreneurship, Education and Culture in the relevant Department.

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