Newsalyze: Effective Communication of Person-Targeting Biases in News Articles

Media bias and its extreme form, fake news, can decisively affect public opinion. Especially when reporting on policy issues, slanted news coverage may strongly influence societal decisions, e.g., in democratic elections. Our paper makes three contributions to address this issue. First, we present a...

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Vydáno v:2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) s. 130 - 139
Hlavní autoři: Hamborg, Felix, Heinser, Kim, Zhukova, Anastasia, Donnay, Karsten, Gipp, Bela
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.09.2021
Témata:
AllSides
Atmospheric measurements
conjoint experiment
Costs
frames
framing
Google News
HCI
Manuals
Natural languages
news aggregator
news bias
Particle measurements
user interface
Visualization
Voting
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Shrnutí:Media bias and its extreme form, fake news, can decisively affect public opinion. Especially when reporting on policy issues, slanted news coverage may strongly influence societal decisions, e.g., in democratic elections. Our paper makes three contributions to address this issue. First, we present a system for bias identification, which combines state-of-the-art methods from natural language understanding. Second, we devise bias-sensitive visualizations to communicate bias in news articles to non-expert news consumers. Third, our main contribution is a large-scale user study that measures bias-awareness in a setting that approximates daily news consumption, e.g., we present respondents with a news overview and individual articles. We not only measure the visualizations' effect on respondents' bias-awareness, but we can also pinpoint the effects on individual components of the visualizations by employing a conjoint design. Our bias-sensitive overviews strongly and significantly increase bias-awareness in respondents. Our study further suggests that our content-driven identification method detects groups of similarly slanted news articles due to substantial biases present in individual news articles. In contrast, the reviewed prior work rather only facilitates the visibility of biases, e.g., by distinguishing left- and right-wing outlets.
DOI:10.1109/JCDL52503.2021.00025