Identifying Informational Sources in News Articles
News articles are driven by the informational sources journalists use in reporting. Modeling when, how and why sources get used together in stories can help us better understand the information we consume and even help journalists with the task of producing it. In this work, we take steps toward this goal by constructing the largest and widest-ranging annotated dataset, to date, of informational sources used in news writing. We show that our dataset can be used to train high-performing models for information detection and source attribution. We further introduce a novel task, source prediction, to study the compositionality of sources in news articles. We show good performance on this task, which we argue is an important proof for narrative science exploring the internal structure of news articles and aiding in planning-based language generation, and an important step towards a source-recommendation system to aid journalists.
Code (1)
Tasks
ArticlesText GenerationSimilar Papers 제목 키워드 기반
Modeling Multi-level Context for Informational Bias Detection by Contrastive Learning and Sentential Graph Network
Informational bias is widely present in news articles. It refers to providing one-sided, selective or suggestive information of specific aspects of certain entity to guide a specific interpretation, thereby biasing the r…
ArticlesBias DetectionContrastive LearningGraph Attention+1Context in Informational Bias Detection
Informational bias is bias conveyed through sentences or clauses that provide tangential, speculative or background information that can sway readers' opinions towards entities. By nature, informational bias is context-d…
ArticlesBias DetectionSentenceIn Plain Sight: Media Bias Through the Lens of Factual Reporting
The increasing prevalence of political bias in news media calls for greater public awareness of it, as well as robust methods for its detection. While prior work in NLP has primarily focused on the lexical bias captured …
Articles365 Dots in 2019: Quantifying Attention of News Sources
We investigate the overlap of topics of online news articles from a variety of sources. To do this, we provide a platform for studying the news by measuring this overlap and scoring news stories according to the degree o…
ArticlesNewsEdits: A Dataset of News Article Revision Histories and a Novel Approach to Document-Level Edit Reasoning
News article revision histories have the potential to give us novel insights across varied fields of linguistics and social sciences. In this work, we present the first publicly available dataset of news revision histori…
ArticlesSentence