Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Classification Aware Neural Topic Model and its Application on a New
  COVID-19 Disinformation Corpus   The explosion of disinformation accompanying the COVID-19 pandemic has
overloaded fact-checkers and media worldwide, and brought a new major challenge
to government responses worldwide. Not only is disinformation creating
confusion about medical science amongst citizens, but it is also amplifying
distrust in policy makers and governments. To help tackle this, we developed
computational methods to categorise COVID-19 disinformation. The COVID-19
disinformation categories could be used for a) focusing fact-checking efforts
on the most damaging kinds of COVID-19 disinformation; b) guiding policy makers
who are trying to deliver effective public health messages and counter
effectively COVID-19 disinformation. This paper presents: 1) a corpus
containing what is currently the largest available set of manually annotated
COVID-19 disinformation categories; 2) a classification-aware neural topic
model (CANTM) designed for COVID-19 disinformation category classification and
topic discovery; 3) an extensive analysis of COVID-19 disinformation categories
with respect to time, volume, false type, media type and origin source.

18
The categories of this paper are: econ
36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
19
The categories of this paper are: eess
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
34
The categories of this paper are: chem-ph
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
35
The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
28
The categories of this paper are: alg-geom
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an