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20212026
most citedEnabling News Consumers to View and Understand Biased News Coverage: A Study on the Perception and Visualization of Media Bias

35 citations · 79 across the 10 of their papers we have counts for

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cs.CL2026

Diverse Word Choices, Same Reference: Annotating Lexically-Rich Cross-Document Coreference

Anastasia Zhukova, Felix Hamborg, Karsten Donnay +2

Cross-document coreference resolution (CDCR) identifies and links mentions of the same entities and events across related documents, enabling content analysis that aggregates infor…

cs.CL20251 cited

What's in the News? Towards Identification of Bias by Commission, Omission, and Source Selection (COSS)

Anastasia Zhukova, Terry Ruas, Felix Hamborg +2

In a world overwhelmed with news, determining which information comes from reliable sources or how neutral is the reported information in the news articles poses a challenge to new…

cs.CL2021

XCoref: Cross-document Coreference Resolution in the Wild

Anastasia Zhukova, Felix Hamborg, Karsten Donnay +1

Datasets and methods for cross-document coreference resolution (CDCR) focus on events or entities with strict coreference relations. They lack, however, annotating and resolving co…

cs.CL20212 cited

Concept Identification of Directly and Indirectly Related Mentions Referring to Groups of Persons

Anastasia Zhukova, Felix Hamborg, Karsten Donnay +1

Unsupervised concept identification through clustering, i.e., identification of semantically related words and phrases, is a common approach to identify contextual primitives emplo…

cs.CL202111 cited

MBIC -- A Media Bias Annotation Dataset Including Annotator Characteristics

T. Spinde, L. Rudnitckaia, K. Sinha +3

Many people consider news articles to be a reliable source of information on current events. However, due to the range of factors influencing news agencies, such coverage may not a…

cs.CL202110 cited

Towards Target-dependent Sentiment Classification in News Articles

Felix Hamborg, Karsten Donnay, Bela Gipp

Extensive research on target-dependent sentiment classification (TSC) has led to strong classification performances in domains where authors tend to explicitly express sentiment ab…