--Context This is the sentiment140 dataset. It contains 1,600,000 tweets extracted using the twitter api. The tweets have been annotated (0 = negative, 4 = positive) and they can be used to detect sentiment.

--Content It contains the following 6 fields:

target: the polarity of the tweet (0 = negative, 2 = neutral, 4 = positive)

ids: The id of the tweet ( 2087)

date: the date of the tweet (Sat May 16 23:58:44 UTC 2009)

flag: The query (lyx). If there is no query, then this value is NO_QUERY.

user: the user that tweeted (robotickilldozr)

text: the text of the tweet (Lyx is cool)

--Acknowledgements The official link regarding the dataset with resources about how it was generated is here The official paper detailing the approach is here

--Citation: Go, A., Bhayani, R. and Huang, L., 2009. Twitter sentiment classification using distant supervision. CS224N Project Report, Stanford, 1(2009), p.12.

--Inspiration To detect severity from tweets. You may have a look at this.

DATASETS:

1. https://www.kaggle.com/datatattle/covid-19-nlp-text-classification
2. https://www.kaggle.com/kazanova/sentiment140

RESOURCES: https://ieeexplore.ieee.org/abstract/document/7427425/