Survey on predicting the Covid-19 cases

COVID-19 is a disease which is caused by a newly discovered coronavirus. Most people infected with the COVID-19 virus will be experience mild to moderate respiratory illness and recover without requiring special treatment. Covid-19 has a strong impact among various people in real life and social media. People have different sentiments regarding the Covid-19 disease. Various techniques are used to identify the status (positive or negative) of people. Techniques such as Convolutional Neural Network, Forward Chaining, etc are used to identify the status of Covid-19 among people. Datasets such as Emolux, COVIDSENTI, CT Scan Images dataset, etc consists of 8, 90,000, 1824 dataset respectively were used in existing systems. After the Survey is done, a system is implemented for the Sentimental Analysis of COVID-19 tweets using the TwitterAPI. The results shows the classification of the tweets into the Score column which includes three categories, Positive, Neutral and Negative tweets. This result is displayed using graphical representation of the Score which can be obtained by calculating Subjectivity and Polarity of a sentence. At the end a word cloud will display the frequency of the words that are used inside the tweets. Data from the various websites can be used in the future for more wide sentimental analysis.