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

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2020
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JCDL '20 : Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020. New York, NY: ACM, 2020, pp. 389-392. ISBN 978-1-4503-7585-6. Available under: doi: 10.1145/3383583.3398619
Zusammenfassung

Traditional media outlets are known to report political news in a biased way, potentially affecting the political beliefs of the audience and even altering their voting behaviors. Many researchers focus on automatically detecting and identifying media bias in the news, but only very few studies exist that systematically analyze how theses biases can be best visualized and communicated. We create three manually annotated datasets and test varying visualization strategies. The results show no strong effects of becoming aware of the bias of the treatment groups compared to the control group, although a visualization of hand-annotated bias communicated bias in-stances more effectively than a framing visualization. Showing participants an overview page, which opposes different viewpoints on the same topic, does not yield differences in respondents' bias perception. Using a multilevel model, we find that perceived journalist bias is significantly related to perceived political extremeness and impartiality of the article.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
320 Politik
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News bias, news slant, bias visualization, perception of news
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JCDL '20 : ACM/IEEE Joint Conference on Digital Libraries in 2020 (Virtual Event), 1. Aug. 2020 - 5. Aug. 2020, Wuhan, China
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ISO 690SPINDE, Timo, Felix HAMBORG, Karsten DONNAY, Angelica BECERRA, Bela GIPP, 2020. Enabling News Consumers to View and Understand Biased News Coverage : A Study on the Perception and Visualization of Media Bias. JCDL '20 : ACM/IEEE Joint Conference on Digital Libraries in 2020 (Virtual Event). Wuhan, China, 1. Aug. 2020 - 5. Aug. 2020. In: JCDL '20 : Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020. New York, NY: ACM, 2020, pp. 389-392. ISBN 978-1-4503-7585-6. Available under: doi: 10.1145/3383583.3398619
BibTex
@inproceedings{Spinde2020Enabl-51333,
  year={2020},
  doi={10.1145/3383583.3398619},
  title={Enabling News Consumers to View and Understand Biased News Coverage : A Study on the Perception and Visualization of Media Bias},
  isbn={978-1-4503-7585-6},
  publisher={ACM},
  address={New York, NY},
  booktitle={JCDL '20 : Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020},
  pages={389--392},
  author={Spinde, Timo and Hamborg, Felix and Donnay, Karsten and Becerra, Angelica and Gipp, Bela}
}
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