Using Artificial Intelligence Applications to Analyze Social Media Users' Sentiment in Real Time of the Coronavirus Pandemic Crisis

Document Type : Original Article

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Journalism lecturer at the Department of Educational Media Faculty of Specific Education - Tanta University

Abstract

The Corona pandemic has led to an important public discussion on social media, and therefore understanding these discussions can help officials and individuals to overcome the epidemic, and the aim of the study was to analyze public feelings towards the outbreak of the Corona virus, and to identify the prevailing topics in discussions related to the virus on Twitter.
This study applied the method of machine learning in the field of artificial intelligence to analyze the data collected from Twitter from March 1 to May 30, 2020, and the study sample included 109,154 tweets. The analyzes included: keyword repetition, sentiment analysis, and topic modeling to identify and explore discussion topics related in real time to the Corona crisis on Twitter over time.
The results resulted in the negative Sentiment outweighing the positive Sentiment in the tweets related to the Coronavirus during the study period, and based on the modeling of the topics, five main topics dominated the Twitter discussions that expressed the users' concerns, and the results also showed that the tweets that were produced in the governorates that were Have lower infection rates that tended to be more positive. Thus, tweets can be used to determine the fluctuations in the severity of the Coronavirus crisis over time.

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