  The COVID-19 pandemic has caused drastic alternations in human life in all
aspects. The government's laws in this regard affected the lifestyle of all
people. Due to this fact studying the sentiment of individuals is essential to
be aware of the future impacts of the coming pandemics. To contribute to this
aim, we proposed an NLP (Natural Language Processing) model to analyze
open-text answers in a survey in Persian and detect positive and negative
feelings of the people in Iran. In this study, a distilBert transformer model
was applied to take on this task. We deployed three approaches to perform the
comparison, and our best model could gain accuracy: 0.824, Precision: 0.824,
Recall: 0.798, and F1 score: 0.804.
