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Title |
Sentiment Analysis of COVID-19 Tweets: Impact of Pre-processing Step |
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Author |
Rami Ayadi, Osama R.Shahin, Osama Ghorbel, Rayan Alanazi, and Anouar Saidi |
| Citation |
Vol. 21 No. 3 pp. 206-211 |
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Abstract |
Internet users are increasingly invited to express their opinions on various subjects in social networks, e-commerce sites, news sites, forums, etc. Much of this information, which describes feelings, becomes the subject of study in several areas of research such as: ""Sensing opinions and analyzing feelings"". It is the process of identifying the polarity of the feelings held in the opinions found in the interactions of Internet users on the web and classifying them as positive, negative, or neutral. In this article, we suggest the implementation of a sentiment analysis tool that has the role of detecting the polarity of opinions from people about COVID-19 extracted from social media (tweeter) in the Arabic language and to know the impact of the pre-processing phase on the opinions classification. The results show gaps in this area of research, first of all, the lack of resources when collecting data. Second, Arabic language is more complexes in pre-processing step, especially the dialects in the pre-treatment phase. But ultimately the results obtained are promising. |
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Keywords |
C.ovid-19, Sentiment Analysis, Covid-19 Tweets, SVM, KNN, pre-processing step, Arabic Language |
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