Detecting Political Bias in News Articles Using Headline Attention

Rama Rohit Reddy Gangula, Suma Reddy Duggenpudi, Radhika Mamidi


Abstract
Language is a powerful tool which can be used to state the facts as well as express our views and perceptions. Most of the times, we find a subtle bias towards or against someone or something. When it comes to politics, media houses and journalists are known to create bias by shrewd means such as misinterpreting reality and distorting viewpoints towards some parties. This misinterpretation on a large scale can lead to the production of biased news and conspiracy theories. Automating bias detection in newspaper articles could be a good challenge for research in NLP. We proposed a headline attention network for this bias detection. Our model has two distinctive characteristics: (i) it has a structure that mirrors a person’s way of reading a news article (ii) it has attention mechanism applied on the article based on its headline, enabling it to attend to more critical content to predict bias. As the required datasets were not available, we created a dataset comprising of 1329 news articles collected from various Telugu newspapers and marked them for bias towards a particular political party. The experiments conducted on it demonstrated that our model outperforms various baseline methods by a substantial margin.
Anthology ID:
W19-4809
Volume:
Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Tal Linzen, Grzegorz Chrupała, Yonatan Belinkov, Dieuwke Hupkes
Venue:
BlackboxNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
77–84
Language:
URL:
https://aclanthology.org/W19-4809
DOI:
10.18653/v1/W19-4809
Bibkey:
Cite (ACL):
Rama Rohit Reddy Gangula, Suma Reddy Duggenpudi, and Radhika Mamidi. 2019. Detecting Political Bias in News Articles Using Headline Attention. In Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, pages 77–84, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Detecting Political Bias in News Articles Using Headline Attention (Gangula et al., BlackboxNLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-4809.pdf