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        <title>Enhancing Bias Detection in Political News Using Pragmatic Presupposition</title>
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    <abstract>Usage of presuppositions in social media and news discourse can be a powerful way to influence the readers as they usually tend to not examine the truth value of the hidden or indirectly expressed information. Fairclough and Wodak (1997) discuss presupposition at a discourse level where some implicit claims are taken for granted in the explicit meaning of a text or utterance. From the Gricean perspective, the presuppositions of a sentence determine the class of contexts in which the sentence could be felicitously uttered. This paper aims to correlate the type of knowledge presupposed in a news article to the bias present in it. We propose a set of guidelines to identify various kinds of presuppositions in news articles and present a dataset consisting of 1050 articles which are annotated for bias (positive, negative or neutral) and the magnitude of presupposition. We introduce a supervised classification approach for detecting bias in political news which significantly outperforms the existing systems.</abstract>
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%0 Conference Proceedings
%T Enhancing Bias Detection in Political News Using Pragmatic Presupposition
%A Kameswari, Lalitha
%A Sravani, Dama
%A Mamidi, Radhika
%Y Ku, Lun-Wei
%Y Li, Cheng-Te
%S Proceedings of the Eighth International Workshop on Natural Language Processing for Social Media
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F kameswari-etal-2020-enhancing
%X Usage of presuppositions in social media and news discourse can be a powerful way to influence the readers as they usually tend to not examine the truth value of the hidden or indirectly expressed information. Fairclough and Wodak (1997) discuss presupposition at a discourse level where some implicit claims are taken for granted in the explicit meaning of a text or utterance. From the Gricean perspective, the presuppositions of a sentence determine the class of contexts in which the sentence could be felicitously uttered. This paper aims to correlate the type of knowledge presupposed in a news article to the bias present in it. We propose a set of guidelines to identify various kinds of presuppositions in news articles and present a dataset consisting of 1050 articles which are annotated for bias (positive, negative or neutral) and the magnitude of presupposition. We introduce a supervised classification approach for detecting bias in political news which significantly outperforms the existing systems.
%R 10.18653/v1/2020.socialnlp-1.1
%U https://aclanthology.org/2020.socialnlp-1.1
%U https://doi.org/10.18653/v1/2020.socialnlp-1.1
%P 1-6

Markdown (Informal)

[Enhancing Bias Detection in Political News Using Pragmatic Presupposition](https://aclanthology.org/2020.socialnlp-1.1) (Kameswari et al., SocialNLP 2020)

• Enhancing Bias Detection in Political News Using Pragmatic Presupposition (Kameswari et al., SocialNLP 2020)

ACL

• Lalitha Kameswari, Dama Sravani, and Radhika Mamidi. 2020. Enhancing Bias Detection in Political News Using Pragmatic Presupposition. In Proceedings of the Eighth International Workshop on Natural Language Processing for Social Media, pages 1–6, Online. Association for Computational Linguistics.