论文标题
量子批评：对情感和命名实体进行分析的标记新闻语料库
Quantum Criticism: A Tagged News Corpus Analysed for Sentiment and Named Entities
论文作者
论文摘要
在这项研究中，我们不断从传统新闻来源的RSS提要中收集数据。我们应用了命名实体识别（NER）工具的几种预训练的实现，从而量化了每个实现的成功。我们还在文档，段落和句子级别对每篇新闻文章进行情感分析，目的是创建标记的新闻文章的语料库，这些文章可通过Web界面提供给公众。最后，我们展示了如何使用该语料库中的数据来识别新闻报道中的偏见。
In this research, we continuously collect data from the RSS feeds of traditional news sources. We apply several pre-trained implementations of named entity recognition (NER) tools, quantifying the success of each implementation. We also perform sentiment analysis of each news article at the document, paragraph and sentence level, with the goal of creating a corpus of tagged news articles that is made available to the public through a web interface. Finally, we show how the data in this corpus could be used to identify bias in news reporting.
