An experimental library for sentimental analysis.
- (hate speech Twitter sentiment analysis)[https://www.kaggle.com/arkhoshghalb/twitter-sentiment-analysis-hatred-speech?select=train.csv]
- training set (31962)
- unbalanced (class 0: 29720, class 1: 2242)
- (Sentiment140)[https://www.kaggle.com/kazanova/sentiment140]
- 1.6 million labelled tweets
- positive and negative and neutral
- from 2009
- (Twitter US Airline Sentiment)[https://www.kaggle.com/crowdflower/twitter-airline-sentiment/]
- 7000+ positive, negative, neutral classified tweets about 7 airlines
- Doesn't contain tweet text, but does contain tweet id so should be able to back query
Note: this section needs to be moved into its own repository where the analysis actually occurs but for now it is a pin in a map of where we are going
Going viral: How a single tweet spawned a COVID-19 conspiracy theory on Twitter Gruzd & Mai\
- (1245104578087059467) One of the propogators of the #FilmYourHospital misinformation campaign
- (1374356089924247553) Tweet calling out Mississippi Health Department for telling an individual that there is not reported evidence that Moderna vaccine works
from Docker
This application can be run using docker. First, open a terminal and build an image
docker build -t <your-image-name> .Then run the image with default jupyter notebooks running
docker run -it -p 8888:8888 -v $PWD/:/app -w /app <your-image-name>If you have pretrained embeddings loaded from somewhere, just run
docker run -it -p 8888:8888 -v $PWD/:/app -w /app -v ~/Dropbox/tweets/model_data/:/embeddings kombucha