Evaluating Trustworthiness of Online News Publishers via Article Classification
CoRR(2024)
摘要
The proliferation of low-quality online information in today's era has
underscored the need for robust and automatic mechanisms to evaluate the
trustworthiness of online news publishers. In this paper, we analyse the
trustworthiness of online news media outlets by leveraging a dataset of 4033
news stories from 40 different sources. We aim to infer the trustworthiness
level of the source based on the classification of individual articles'
content. The trust labels are obtained from NewsGuard, a journalistic
organization that evaluates news sources using well-established editorial and
publishing criteria. The results indicate that the classification model is
highly effective in classifying the trustworthiness levels of the news
articles. This research has practical applications in alerting readers to
potentially untrustworthy news sources, assisting journalistic organizations in
evaluating new or unfamiliar media outlets and supporting the selection of
articles for their trustworthiness assessment.
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