covid19-tweets

Analyzing Covid19 Tweets

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Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
.deepnote		.deepnote
1.1. clean & filter english tweets.ipynb		1.1. clean & filter english tweets.ipynb
1.2. clean text, tags & date.ipynb		1.2. clean text, tags & date.ipynb
1.3. clean & get_embeddings.ipynb		1.3. clean & get_embeddings.ipynb
1.4. clean sentiment data.ipynb		1.4. clean sentiment data.ipynb
2.1. visualize embedding space.ipynb		2.1. visualize embedding space.ipynb
2019.csv		2019.csv
3.1. sentiment linear regression.ipynb		3.1. sentiment linear regression.ipynb
3.2. sentiment logistic regression.ipynb		3.2. sentiment logistic regression.ipynb
3.3. sentiment LDA.ipynb		3.3. sentiment LDA.ipynb
4.1 geographic visualization of tweets.ipynb		4.1 geographic visualization of tweets.ipynb
Data_cleaning,_preparation,_and_understanding.ipynb		Data_cleaning,_preparation,_and_understanding.ipynb
README.md		README.md
[Cleaned].ipynb		[Cleaned].ipynb
covid19_tweets.csv		covid19_tweets.csv
covid_predictions.csv		covid_predictions.csv
covid_predictions_with_proba.csv		covid_predictions_with_proba.csv
data_country_random.csv		data_country_random.csv
english_tweets.csv		english_tweets.csv
init.ipynb		init.ipynb
points.geojson		points.geojson
requirements.txt		requirements.txt
sentiment_data.zip		sentiment_data.zip
target.npy		target.npy
test.ipynb		test.ipynb
vectorized_100.npy		vectorized_100.npy
vectorized_200.npy		vectorized_200.npy
vectorized_300.npy		vectorized_300.npy
vectorized_50.npy		vectorized_50.npy
word1.png		word1.png

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