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:Covid-19大流行对我们的生活产生了巨大影响,特别是对人们的相互作用产生了巨大影响。通过引入Covid-19疫苗,对是否接种疫苗的问题提出了积极和消极的意见。在本文中,我们利用从Twitter收集的数据,包括推特和用户简介,对伊朗关于Corona病毒疫苗的公众舆论进行了全面分析。为此目的,我们运用了搜索查询技术,同时采用一个主题模型方法来提取与疫苗有关的推文。我们利用基于变压器的模型来分类推文的内容,并提取围绕疫苗循环的主题。我们还进行了情感分析,以评价围绕这个主题的公共幸福和愤怒。我们的结果表明,Covid-19疫苗从不同的角度吸引了相当大的关注,例如政府问题、安全或头目以及副作用。此外,Corona病毒相关现象,例如公共疫苗接种以及受严重影响的公共情感状况和用户互动的感染率。