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

Zhukova, Anastasia, Ruas, Terry, Hamborg, Felix, Donnay, Karsten, Gipp, Bela

arXiv.org Artificial Intelligence 

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 news readers. In this paper, we propose a methodology for automatically identifying bias by commission, omission, and source selection (COSS) as a joint three-fold objective, as opposed to the previous work separately addressing these types of bias. In a pipeline concept, we describe the goals and tasks of its steps toward bias identification and provide an example of a visualization that leverages the extracted features and patterns of text reuse.

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