The Covid-19 pandemic had an enormous effect on our lives, especially on people's interactions. By introducing Covid-19 vaccines, both positive and negative opinions were raised over the subject of taking vaccines or not. In this paper, using data gathered from Twitter, including tweets and user profiles, we offer a comprehensive analysis of public opinion in Iran about the Coronavirus vaccines. For this purpose, we applied a search query technique combined with a topic modeling approach to extract vaccine-related tweets. We utilized transformer-based models to classify the content of the tweets and extract themes revolving around vaccination. We also conducted an emotion analysis to evaluate the public happiness and anger around this topic. Our results demonstrate that Covid-19 vaccination has attracted considerable attention from different angles, such as governmental issues, safety or hesitancy, and side effects. Moreover, Coronavirus-relevant phenomena like public vaccination and the rate of infection deeply impacted public emotional status and users' interactions.

翻译：新冠大流行对我们的生活产生了巨大影响，尤其是对人们的互动方面。随着新冠疫苗的推出，关于是否接种疫苗的问题引发了正面和负面的意见。本文利用从Twitter收集的数据（包括推文和用户资料），对伊朗公众对新冠疫苗的观点进行了全面分析。为此，我们结合搜索查询技术和主题建模方法来提取与疫苗相关的推文。我们采用基于Transformer的模型对推文内容进行分类，并提取围绕疫苗接种的主题。我们还进行了情感分析，以评估公众对此话题的喜悦和愤怒程度。我们的结果表明，新冠疫苗接种从多个角度吸引了广泛关注，例如政府问题、安全性或犹豫态度以及副作用。此外，与新冠病毒相关的现象（如公众接种率和感染率）深刻影响了公众情绪状态和用户互动。