  Healthcare workers such as doctors and nurses are expected to be trustworthy
and creditable sources of vaccine-related information. Their opinions toward
the COVID-19 vaccines may influence the vaccine uptake among the general
population. However, vaccine hesitancy is still an important issue even among
the healthcare workers. Therefore, it is critical to understand their opinions
to help reduce the level of vaccine hesitancy. There have been studies
examining healthcare workers' viewpoints on COVID-19 vaccines using
questionnaires. Reportedly, a considerably higher proportion of vaccine
hesitancy is observed among nurses, compared to doctors. We intend to verify
and study this phenomenon at a much larger scale and in fine grain using social
media data, which has been effectively and efficiently leveraged by researchers
to address real-world issues during the COVID-19 pandemic. More specifically,
we use a keyword search to identify healthcare workers and further classify
them into doctors and nurses from the profile descriptions of the corresponding
Twitter users. Moreover, we apply a transformer-based language model to remove
irrelevant tweets. Sentiment analysis and topic modeling are employed to
analyze and compare the sentiment and thematic differences in the tweets posted
by doctors and nurses. We find that doctors are overall more positive toward
the COVID-19 vaccines. The focuses of doctors and nurses when they discuss
vaccines in a negative way are in general different. Doctors are more concerned
with the effectiveness of the vaccines over newer variants while nurses pay
more attention to the potential side effects on children. Therefore, we suggest
that more customized strategies should be deployed when communicating with
different groups of healthcare workers.
