Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Twitter Sent Dnn | 263 | 4 years ago | 9 | mit | Python | |||||
Deep Neural Network for Sentiment Analysis on Twitter | ||||||||||
Geolocation | 30 | 3 years ago | 1 | gpl-3.0 | Python | |||||
Geolocation prediction for a given Tweet | ||||||||||
Deep Learning Tweets Text Classifier Word2vec | 22 | 7 years ago | Python | |||||||
This tool uses Word2Vec combined with Neural Networks, SVM, KNN, Naive Bayes, Decision Trees and ExtraTrees. This was used on Twitter for classifying tweets. | ||||||||||
Simple Sentiment Analysis | 21 | 4 years ago | Python | |||||||
Simple text polarity classifier on Python | ||||||||||
Ironydetectionintwitter | 16 | 6 years ago | Python | |||||||
A Simple and Accurate Neural Network Model for Irony Detection in Twitter | ||||||||||
Kaggle Twitter Sentiment Analysis | 15 | 6 years ago | 1 | Python | ||||||
Kaggle Twitter Sentiment Analysis Competition | ||||||||||
Ensemble Learning For Tweet Classification Of Hate Speech And Offensive Language | 10 | 6 years ago | Python | |||||||
Contains code for a voting classifier that is part of an ensemble learning model for tweet classification (which includes an LSTM, a bayesian model and a proximity model) and a system for weighted voting | ||||||||||
Neural_emotion_intensity_prediction | 9 | 6 years ago | 1 | Jupyter Notebook | ||||||
The code for our proposed neural models which give state-of-the-art performance for emotion intensity detection in tweets. | ||||||||||
Tweetgenerator | 8 | 5 years ago | Jupyter Notebook | |||||||
Neural network for writing tweets like @realDonaldTrump based on transfer learning | ||||||||||
Twitter Sentiment Analysis | 8 | 4 years ago | 3 | Jupyter Notebook | ||||||
This project develops a deep learning model that trains on 1.6 million tweets for sentiment analysis to classify any new tweet as either being positive or negative. |