Header

UZH-Logo

Maintenance Infos

Enabling news consumers to view and understand biased news coverage: a study on the perception and visualization of media bias


Spinde, Timo; Hamborg, Felix; Donnay, Karsten; Becerra, Angelica; Gipp, Bela (2020). Enabling news consumers to view and understand biased news coverage: a study on the perception and visualization of media bias. In: Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, Virtual Event China, 1 August 2020 - 5 August 2020, 389-392.

Abstract

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.

Abstract

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.

Statistics

Citations

Dimensions.ai Metrics

Altmetrics

Downloads

1 download since deposited on 06 Jan 2021
1 download since 12 months
Detailed statistics

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Political Science
Dewey Decimal Classification:320 Political science
Scopus Subject Areas:Physical Sciences > General Engineering
Uncontrolled Keywords:news bias, news slant, bias visualization, perception of news
Language:English
Event End Date:5 August 2020
Deposited On:06 Jan 2021 14:46
Last Modified:07 Jan 2021 21:01
ISBN:978-1-4503-7585-6
Additional Information:JCDL '20: The ACM/IEEE Joint Conference on Digital Libraries in 2020 Autor der Publikation: Huang, Ruhua Publisher: Association for Computing Machinery, New York, NY
OA Status:Closed
Publisher DOI:https://doi.org/10.1145/3383583.3398619
Related URLs:https://dl.acm.org/doi/proceedings/10.1145/3383583 (Organisation)

Download

Closed Access: Download allowed only for UZH members