Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Framework para Caracterizar Fake News en Terminos de Emociones   Social networks have become one of the main information channels for human
beings due to the immediate and social interactivity they offer, allowing in
some cases to publish what each user considers relevant. This has brought with
it the generation of false news or Fake News, publications that only seek to
generate uncertainty, misinformation or skew the opinion of readers. It has
been shown that the human being is not capable of fully identifying whether an
article is really a fact or a Fake News, due to this it is that models arise
that seek to characterize and identify articles based on data mining and
machine learning. This article proposes a three-layer framework, the main
objective of which is to characterize the emotions present in Fake News and to
be a tool for future work that identifies the emotional state and intentional
state of the public.

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The categories of this paper are: quant-ph
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
29
The categories of this paper are: funct-an
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The categories of this paper are: acc-phys
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
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The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
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The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
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The categories of this paper are: nlin
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The categories of this paper are: dg-ga
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The categories of this paper are: math-ph
3
The categories of this paper are: physics