  At the time of this study, the SARS-CoV-2 virus that caused the COVID-19
pandemic has spread significantly across the world. Considering the uncertainty
about policies, health risks, financial difficulties, etc. the online media,
specially the Twitter platform, is experiencing a high volume of activity
related to this pandemic. Among the hot topics, the polarized debates about
unconfirmed medicines for the treatment and prevention of the disease have
attracted significant attention from online media users. In this work, we
present a stance data set, COVID-CQ, of user-generated content on Twitter in
the context of COVID-19. We investigated more than 14 thousand tweets and
manually annotated the opinions of the tweet initiators regarding the use of
"chloroquine" and "hydroxychloroquine" for the treatment or prevention of
COVID-19. To the best of our knowledge, COVID-CQ is the first data set of
Twitter users' stances in the context of the COVID-19 pandemic, and the largest
Twitter data set on users' stances towards a claim, in any domain. We have made
this data set available to the research community via GitHub. We expect this
data set to be useful for many research purposes, including stance detection,
evolution and dynamics of opinions regarding this outbreak, and changes in
opinions in response to the exogenous shocks such as policy decisions and
events.
