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.
翻译:COVID-19大流行造成了人类生活各方面的巨大变化,政府在这方面的法律影响到所有人的生活方式。由于这个事实,研究个人情绪对于了解即将到来的流行病的未来影响至关重要。为了实现这一目标,我们提议了一个NLP(语言处理)模式,在波斯调查中分析公开文本回答,发现伊朗人民的正面和负面情绪。在这项研究中,采用了一种分解变异器模式来承担这项任务。我们采用了三种方法来进行比较,我们的最佳模式可以准确化:0.824, 精准度:0.824, 回溯:0.798, F1分:0.804。