Sentimental Tweets Classification of Symptomatic COVID 19
P, T.
Show abstract
The approach I described is straightforward, related to COVID-19 SARS based tweets and the symptoms, that people tweet about. Also, social media mining for health application reports was shared in many different tasks of 2021. The motto at the back of this observe is to analyses tweets of COVID-19 based symptoms. By performing BERT model and text classification with XLNET with which uses to classify text and purpose of the texts (i.e.) tweets. So that I can get a deep understanding of the texts. When developing the system, I used two models the XLNet and DistilBERT for the text sorting task, but the outcome was XLNET out-performs the given approach to the best accuracy achieved. Now I discover a whole lot vital for as it should be categorizing tweets as encompassing self-said COVID-19 indications. Whether or not a tweets associated with COVID-19 is a non-public report or an information point out to the virus. Which gives test accuracy to an F1 score of 96%.
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