Sentiment Analysis of COVID-19 Tweets: Impact of Pre-processing Step

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 preprocessing 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