Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fake News Detection: a comparison between available Deep Learning
  techniques in vector space   Fake News Detection is an essential problem in the field of Natural Language
Processing. The benefits of an effective solution in this area are manifold for
the goodwill of society. On a surface level, it broadly matches with the
general problem of text classification. Researchers have proposed various
approaches to tackle fake news using simple as well as some complex techniques.
In this paper, we try to make a comparison between the present Deep Learning
techniques by representing the news instances in some vector space using a
combination of common mathematical operations with available vector space
representations. We do a number of experiments using various combinations and
permutations. Finally, we conclude with a sound analysis of the results and
evaluate the reasons for such results.

8
The categories of this paper are: hep-ex
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
12
The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th
31
The categories of this paper are: ao-sci
28
The categories of this paper are: alg-geom
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph