Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Heuristic-driven Ensemble Framework for COVID-19 Fake News Detection   The significance of social media has increased manifold in the past few
decades as it helps people from even the most remote corners of the world stay
connected. With the COVID-19 pandemic raging, social media has become more
relevant and widely used than ever before, and along with this, there has been
a resurgence in the circulation of fake news and tweets that demand immediate
attention. In this paper, we describe our Fake News Detection system that
automatically identifies whether a tweet related to COVID-19 is "real" or
"fake", as a part of CONSTRAINT COVID19 Fake News Detection in English
challenge. We have used an ensemble model consisting of pre-trained models that
has helped us achieve a joint 8th position on the leader board. We have
achieved an F1-score of 0.9831 against a top score of 0.9869. Post completion
of the competition, we have been able to drastically improve our system by
incorporating a novel heuristic algorithm based on username handles and link
domains in tweets fetching an F1-score of 0.9883 and achieving state-of-the art
results on the given dataset.

6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
28
The categories of this paper are: alg-geom
20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
18
The categories of this paper are: econ
23
The categories of this paper are: solv-int
16
The categories of this paper are: stat
21
The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci