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Using machine learning to predict the sentiment of arabic tweets related to covid-19
Author(s):
1. ESLAM AL MAGHAYREH: College of Applied Computer Science, King Saud University, KSA; Computer Science Department, Yarmouk University, Jordan
Abstract:
The world has suffered a lot due to the spread of the COVID-19 virus. The world health organization (WHO) declared the COVID-19 pandemic a global emergency. The governments and healthcare officials everywhere were fighting to control the spread of this pandemic. Meanwhile, a considerable amount of social media data (e.g., tweets) related to COVID-19 is being generated continuously. In this paper, we will build a model that can identify the sentiment of Twitter data related to COVID-19 using machine learning. We will focus on analyzing Arabic language tweets to determine people's opinions, feelings, and status on the impact of COVID-19. The main objective of this research is to support efforts to study the impact of the COVID-19 pandemic on society. To achieve this objective, we have prepared a dataset of Arabic tweets related to COVID-19 and manually classified the tweets in the dataset. Then we have used machine learning to develop an approach to assess people's feelings about COVID-19. This approach can help the government and healthcare officials to identify any negative and positive aspects of this crisis to improve their response to similar future crises.
Page(s): 5368-5375
DOI: DOI not available
Published: Journal: Journal of Theoretical and Applied Information Technology, Volume: 100, Issue: 14, Year: 2022
Keywords:
Sentiment analysis , Text Analysis , natural language processing , Machine learning , Data Science
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