Publication: Automated identification of bias inducing words in news articles using linguistic and context-oriented features
Automated identification of bias inducing words in news articles using linguistic and context-oriented features
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Spinde, T., Rudnitckaia, L., Mitrović, J., Hamborg, F., Granitzer, M., Gipp, B., & Donnay, K. (2021). Automated identification of bias inducing words in news articles using linguistic and context-oriented features. Information Processing & Management, 58(3), 102505. https://doi.org/10.1016/j.ipm.2021.102505
Abstract
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Media has a substantial impact on public perception of events, and, accordingly, the way media presents events can potentially alter the beliefs and views of the public. One of the ways in which bias in news articles can be introduced is by altering word choice. Such a form of bias is very challenging to identify automatically due to the high context-dependence and the lack of a large-scale gold-standard data set. In this paper, we present a prototypical yet robust and diverse data set for media bias research. It consists of 1,700 sta
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- Spinde, Timo
- Rudnitckaia, Lada
- Mitrović, Jelena
- Hamborg, Felix
- Granitzer, Michael
- Gipp, Bela
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Spinde, T., Rudnitckaia, L., Mitrović, J., Hamborg, F., Granitzer, M., Gipp, B., & Donnay, K. (2021). Automated identification of bias inducing words in news articles using linguistic and context-oriented features. Information Processing & Management, 58(3), 102505. https://doi.org/10.1016/j.ipm.2021.102505
