--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:
- https://www.kaggle.com/datatattle/covid-19-nlp-text-classification
- https://www.kaggle.com/kazanova/sentiment140
RESOURCES: https://ieeexplore.ieee.org/abstract/document/7427425/