Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: In Search of Credible News   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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The categories of this paper are: quant-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: gr-qc
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The categories of this paper are: stat
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The categories of this paper are: atom-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: supr-con
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The categories of this paper are: astro-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-lat
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The categories of this paper are: nucl-th
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The categories of this paper are: nucl-ex
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The categories of this paper are: q-alg
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The categories of this paper are: q-bio
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The categories of this paper are: math-ph
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The categories of this paper are: hep-ex