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2016 | OriginalPaper | Buchkapitel

In Search of Credible News

verfasst von : Momchil Hardalov, Ivan Koychev, Preslav Nakov

Erschienen in: Artificial Intelligence: Methodology, Systems, and Applications

Verlag: Springer International Publishing

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Abstract

We study the problem of finding fake online news. This is an important problem as news of questionable credibility have recently been proliferating in social media at an alarming scale. As this is an understudied problem, especially for languages other than English, we first collect and release to the research community three new balanced credible vs. fake news datasets derived from four online sources. We then propose a language-independent approach for automatically distinguishing credible from fake news, based on a rich feature set. In particular, we use linguistic (n-gram), credibility-related (capitalization, punctuation, pronoun use, sentiment polarity), and semantic (embeddings and DBPedia data) features. Our experiments on three different testsets show that our model can distinguish credible from fake news with very high accuracy.

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Metadaten
Titel
In Search of Credible News
verfasst von
Momchil Hardalov
Ivan Koychev
Preslav Nakov
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-44748-3_17