Document Type : Research Paper

Authors

1 Assistant Professor, Department of Computer Engineering, Shahrekord University, Shahrekord, Iran(Corresponding Author: basiri@sku.ac.ir).

2 Department of Computer Eng., Faculty of Engineering, Shahrekord University, Iran

3 Department of Computer Engineering, Faculty of Engineering, Shahrekord University, Iran

Abstract

With the spread of Covid-19 disease, quarantine, and social isolation, people are increasingly posting their opinions about the coronavirus on social networks such as Twitter. However, no study has yet been reported to analyze online opinions of individuals in order to understand their feelings about the Covid-19 epidemic in Iran. This study analyzes the emotions in the opinions of the Iranian people on the social network Twitter during the Corona crisis. For this purpose, a deep neural network model is presented. As there is no labeled dataset of Covid-19 tweets, the proposed model is first trained on the Stanford University Sentiment140 dataset, which contains 1.6 million tweets, and then used to classify the two classes of emotions contained in the collected corona-related tweets in Iran. The results show that the percentage of tweets with negative emotions is significantly higher than positive tweets. Also, the change in negative emotions of people in different months is proportional to the change in patient statistics.

Keywords

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استناد به این مقاله: بصیری، محمد احسان، حبیبی، شیرین، نعمتی، شهلا. (1400). تحلیل احساسات توئیت‌های مرتبط با کرونا در ایران با استفاده از شبکه عصبی عمیق، مطالعات مدیریت کسب وکار هوشمند، 10(37)، 109-134.                                                  DOI: 10.22054/IMS.2021.54705.1799
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