Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The relationship between sentiment score and COVID-19 cases in the
  United States   The coronavirus disease (COVID-19) continues to have devastating effects
across the globe. No nation has been free from the uncertainty brought by this
pandemic. The health, social and economic tolls associated with it are causing
strong emotions and spreading fear in people of all ages, genders, and races.
Since the beginning of the COVID-19 pandemic, many have expressed their
feelings and opinions related to a wide range of aspects of their lives via
Twitter. In this study, we consider a framework for extracting sentiment scores
and opinions from COVID-19 related tweets. We connect users' sentiment with
COVID-19 cases across the USA and investigate the effect of specific COVID-19
milestones on public sentiment. The results of this work may help with the
development of pandemic-related legislation, serve as a guide for scientific
work, as well as inform and educate the public on core issues related to the
pandemic.

4
The categories of this paper are: cond-mat
9
The categories of this paper are: nlin
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
26
The categories of this paper are: bayes-an
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an