Quantifying Global Foreign Affairs with a Multimodal Dataset of Diplomatic Websites

This research introduces a global dataset of diplomatic news and images compiled from the official webpages of ministries of foreign affairs and chief executive offices across 156 countries spanning over 20 years. The collection provides over 1.16 million news articles and 1.18 million associated images. Our research initially shows how web scraping and Natural Language Processing (NLP) tools enhance labor-saving, novel data acquisition and processing methods. First, we extracted named entities for people, countries, and organizations mentioned in diplomatic texts. Second, GlobalDiplomacyNET processes and analyzes images published on diplomatic webpages, capturing governments' image-sharing practices. This textual and visual information together provides substantial information on countries' news-sharing habits, geographical and multilateral attention, visual assertiveness, and gender representation. GlobalDiplomacyNET is the first of its kind, offering a global corpus of textual and visual data that support novel research directions particularly in international relations and political science.

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Publication Details

Journal
Scientific Data
Published
2025-11-28
DOI
https://doi.org/10.1038/s41597-025-06334-5
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Quantifying Global Foreign Affairs with a Multimodal Dataset of Diplomatic Websites

Ali Gökhan Demir, Ni̇hat Muğurtay, Onur Varol, Beste Bahçeci et al.
Scientific Data
Computational and Text Analysis Methods
article

Quantifying Global Foreign Affairs with a Multimodal Dataset of Diplomatic Websites

Ali Gökhan Demir, Ni̇hat Muğurtay, Onur Varol, Beste Bahçeci, Yasser Zouzou, Meltem Müftüler-Baç, Mehrdad Heshmat Najafabad, Ahmet Taha Kahya, Fazlı Göktuğ Yılmaz, Doğukan Tosun, Kaan Güray Şirin
article en

Abstract

This research introduces a global dataset of diplomatic news and images compiled from the official webpages of ministries of foreign affairs and chief executive offices across 156 countries spanning over 20 years. The collection provides over 1.16 million news articles and 1.18 million associated images. Our research initially shows how web scraping and Natural Language Processing (NLP) tools enhance labor-saving, novel data acquisition and processing methods. First, we extracted named entities for people, countries, and organizations mentioned in diplomatic texts. Second, GlobalDiplomacyNET processes and analyzes images published on diplomatic webpages, capturing governments' image-sharing practices. This textual and visual information together provides substantial information on countries' news-sharing habits, geographical and multilateral attention, visual assertiveness, and gender representation. GlobalDiplomacyNET is the first of its kind, offering a global corpus of textual and visual data that support novel research directions particularly in international relations and political science.

Scientific DataVol. 12(1)
Sabancı Üniversitesi (TR)
Openalex Percentile: Top 53%
Computational and Text Analysis Methods
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