Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Characterizing drug mentions in COVID-19 Twitter Chatter   Since the classification of COVID-19 as a global pandemic, there have been
many attempts to treat and contain the virus. Although there is no specific
antiviral treatment recommended for COVID-19, there are several drugs that can
potentially help with symptoms. In this work, we mined a large twitter dataset
of 424 million tweets of COVID-19 chatter to identify discourse around drug
mentions. While seemingly a straightforward task, due to the informal nature of
language use in Twitter, we demonstrate the need of machine learning alongside
traditional automated methods to aid in this task. By applying these
complementary methods, we are able to recover almost 15% additional data,
making misspelling handling a needed task as a pre-processing step when dealing
with social media data.

37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
20
The categories of this paper are: acc-phys
17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
16
The categories of this paper are: stat
18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
27
The categories of this paper are: comp-gas
34
The categories of this paper are: chem-ph
8
The categories of this paper are: hep-ex