@inproceedings{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},

author = {Timo Spinde and Felix Hamborg and Karsten Donnay and Angelica Becerra and Bela Gipp},

url = {https://doi.org/10.1145/3383583.3398619},

doi = {10.1145/3383583.3398619},

isbn = {9781450375856},

year  = {2020},

date = {2020-01-01},

booktitle = {Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020},

pages = {389–392},

publisher = {Association for Computing Machinery},

address = {Virtual Event, China},

series = {JCDL '20},

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.},

keywords = {bias visualization, news bias, news slant, perception of news},

pubstate = {published},

tppubtype = {inproceedings}

}