德国新闻文章的地理位置数据集
Lukas Kriesch1, Sebastian Losacker2,3
1Department of Geography, Justus Liebig University Giessen, Senckenbergstr. 1, 35390, Giessen, Germany. lukas.kriesch@geogr.uni-giessen.de.
Scientific data
|July 2, 2025
概括
本研究介绍了一种使用大型语言模型地理定位和分析新闻文章的方法. 研究人员现在可以访问5000万个德国新闻文章的数据集,其中包含位置数据和文本嵌入,用于高级社会科学研究.
科学领域:
- 社会科学 社会科学 社会科学
- 计算语言学 计算语言学
- 数据科学数据科学数据科学
背景情况:
- 数字化文本数据和大型语言模型 (LLM) 正在改变社会科学研究.
- 新闻数据提供了对公共话语和社会趋势的实时洞察.
- 地理定位和分析新闻内容对于理解时空动态至关重要.
研究的目的:
- 提出一个可复制的方法,用于地理定位和分析新闻文章.
- 创建一个全面的数据集的地理位置德国新闻文章与文本嵌入.
- 为了促进高级语义搜索和分析大型新闻公司.
主要方法:
- 从CommonCrawl News数据集和文本清理中收集数据.
- 命名实体识别 (NER) 用于地理编码新闻文章来源.
- 句子-BERT (SBERT) 用于将新闻文本转化为语义嵌入.
主要成果:
- 收集了大约5000万个德国新闻文章的数据集.
- 数据集中的约70%的文章包含可识别的地理位置.
- 嵌入文本可以在新闻库中进行高效的语义搜索.
结论:
- 开发的方法提供了一个强大的框架,用于地理定位和分析新闻数据.
- 公开可用的德国新闻数据集和嵌入式支持各种社会科学调查.
- 这种方法可以适应来自其他国家的新闻数据,促进全球研究.
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