用外交网站的多模式数据集量化全球外交事务
Nihat Muğurtay1,2, Kaan Güray Şirin3, Mehrdad Heshmat Najafabad3
1Faculty of Arts and Social Sciences, Sabanci University, Istanbul, Türkiye. nihat.mugurtay@sabanciuniv.edu.
Scientific data
|November 29, 2025
概括
本研究介绍了GlobalDiplomacyNET,这是一个新的全球外交新闻和图像数据集. 它使用自然语言处理 (NLP) 和网络抓取来分析政府的沟通实践.
科学领域:
- 国际关系 国际关系
- 政治科学 政治科学是指政治学.
- 计算社会科学 计算社会科学
背景情况:
- 外交沟通越来越数字化,但大规模的多式联运数据集很少.
- 了解政府信息传播需要分析文本和视觉内容.
- 现有的研究缺乏关于外交信息的全面全球数据.
研究的目的:
- 介绍GlobalDiplomacyNET,这是第一个全球外交新闻和图像集.
- 展示使用网络抓取和NLP的新型数据采集和处理方法.
- 为了使国际关系和政治科学的新研究.
主要方法:
- 搜索156个国家的官方外交部和行政办公室网页.
- 自然语言处理 (NLP) 用于命名实体识别 (人,国家,组织).
- 图像分析以捕捉政府的图像共享实践和视觉通信.
主要成果:
- 一个包含超过116万篇新闻文章和118万张相关图像的数据集,跨越20多年的时间.
- 提取关键实体并分析文本和视觉外交内容.
- 了解各国的新闻分享习惯,地理重点,视觉自信和性别代表性.
结论:
- 全球外交网 (GlobalDiplomacyNET) 为研究全球外交实践提供了一个独特的资源.
- 该数据集支持国际关系和政治学领域的新研究方向.
- 自动化数据采集和分析方法显著推进了社会科学研究.
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