  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 instances 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.

Computers and Society