ArticleScientific data2025
Quantifying Global Foreign Affairs with a Multimodal Dataset of Diplomatic Websites.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
11 authors.
Funding
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.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.