Publikation:

Enhancing media literacy : The effectiveness of (Human) annotations and bias visualizations on bias detection

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Datum

2025

Autor:innen

Wu, Fei
Demartini, Gianluca
Echizen, Isao

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Deutsche Forschungsgemeinschaft (DFG): 441541975

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Open Access-Veröffentlichung
Open Access Hybrid
Core Facility der Universität Konstanz

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Published

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Information Processing & Management. Elsevier. 2025, 62(6), 104244. ISSN 0306-4573. eISSN 1873-5371. Verfügbar unter: doi: 10.1016/j.ipm.2025.104244

Zusammenfassung

Marking biased texts effectively increases media bias awareness, but its sustainability across new topics and unmarked news remains unclear, and the role of AI-generated bias labels is untested. This study examines how news consumers learn to perceive media bias from human- and AI-generated labels and identify biased language through highlighting, neutral rephrasing, and political orientation cues. We conducted two experiments with a teaching phase exposing them to various bias-labeling conditions and a testing phase evaluating their ability to classify biased sentences and detect biased text in unlabeled news on new topics.

We find that, compared to the control group, both human- and AI-generated sentential bias labels significantly improve bias classification (p < .001), though human labels are more effective (d = 0.42 vs. d = 0.23). Additionally, among all teaching interventions, participants best detect biased sentences when taught with biased sentence or phrase labels (p < .001), while politicized phrase labels reduce accuracy. The effectiveness of different media literacy interventions remains independent of political ideology, but conservative participants are generally less accurate (p = .011), suggesting an interaction between political inclinations and bias detection.

Our research provides a novel experimental framework into assessing the generalizability of media bias awareness and offer practical implications for designing bias indicators in news-reading platforms and media literacy curricula.

Zusammenfassung in einer weiteren Sprache

Fachgebiet (DDC)
150 Psychologie

Schlagwörter

News literacy, Media bias, Language processing, Text perception

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ISO 690SPINDE, Timo, Fei WU, Wolfgang GAISSMAIER, Gianluca DEMARTINI, Isao ECHIZEN, Helge GIESE, 2025. Enhancing media literacy : The effectiveness of (Human) annotations and bias visualizations on bias detection. In: Information Processing & Management. Elsevier. 2025, 62(6), 104244. ISSN 0306-4573. eISSN 1873-5371. Verfügbar unter: doi: 10.1016/j.ipm.2025.104244
BibTex
@article{Spinde2025-11Enhan-73690,
  title={Enhancing media literacy : The effectiveness of (Human) annotations and bias visualizations on bias detection},
  year={2025},
  doi={10.1016/j.ipm.2025.104244},
  number={6},
  volume={62},
  issn={0306-4573},
  journal={Information Processing & Management},
  author={Spinde, Timo and Wu, Fei and Gaissmaier, Wolfgang and Demartini, Gianluca and Echizen, Isao and Giese, Helge},
  note={Article Number: 104244}
}
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We find that, compared to the control group, both human- and AI-generated sentential bias labels significantly improve bias classification (p &lt; .001), though human labels are more effective (d = 0.42 vs. d = 0.23). Additionally, among all teaching interventions, participants best detect biased sentences when taught with biased sentence or phrase labels (p &lt; .001), while politicized phrase labels reduce accuracy. The effectiveness of different media literacy interventions remains independent of political ideology, but conservative participants are generally less accurate (p = .011), suggesting an interaction between political inclinations and bias detection.

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