Quantifying Political Bias in News Articles
Gizem Gezici
TL;DR
This paper investigates the challenge of automatically quantifying ideological bias in online news articles and search results, highlighting current model limitations in reliably annotating bias.
Contribution
The study introduces an automated approach for evaluating political bias in news articles and analyzes the effectiveness of existing models.
Findings
Current models are insufficient for automatic bias annotation.
Automated bias evaluation remains a challenging task.
The dataset includes search result articles and newspaper articles.
Abstract
Search bias analysis is getting more attention in recent years since search results could affect In this work, we aim to establish an automated model for evaluating ideological bias in online news articles. The dataset is composed of news articles in search results as well as the newspaper articles. The current automated model results show that model capability is not sufficient to be exploited for annotating the documents automatically, thereby computing bias in search results.
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Taxonomy
TopicsMisinformation and Its Impacts · Sentiment Analysis and Opinion Mining · Hate Speech and Cyberbullying Detection