  Hydroxychloroquine (HCQ) is used to prevent or treat malaria caused by
mosquito bites. Recently, the drug has been suggested to treat COVID-19, but
that has not been supported by scientific evidence. The information regarding
the drug efficacy has flooded social networks, posting potential threats to the
community by perverting their perceptions of the drug efficacy. This paper
studies the reactions of social network users on the recommendation of using
HCQ for COVID-19 treatment by analyzing the reaction patterns and sentiment of
the tweets. We collected 164,016 tweets from February to December 2020 and used
a text mining approach to identify social reaction patterns and opinion change
over time. Our descriptive analysis identified an irregularity of the users'
reaction patterns associated tightly with the social and news feeds on the
development of HCQ and COVID-19 treatment. The study linked the tweets and
Google search frequencies to reveal the viewpoints of local communities on the
use of HCQ for COVID-19 treatment across different states. Further, our tweet
sentiment analysis reveals that public opinion changed significantly over time
regarding the recommendation of using HCQ for COVID-19 treatment. The data
showed that high support in the early dates but it significantly declined in
October. Finally, using the manual classification of 4,850 tweets by humans as
our benchmark, our sentiment analysis showed that the Google Cloud Natural
Language algorithm outperformed the Valence Aware Dictionary and sEntiment
Reasoner in classifying tweets, especially in the sarcastic tweet group.
