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Identifying Tweets with Adverse Drug Reactions.
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A WEKA package for analyzing emotion and sentiment of tweets.
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thefirebanks/Ensemble-Learning-for-Tweet-Classification-of-Hate-Speech-and-Offensive-Language 10 0 0 almost 8 years ago 0 0 Python
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Pranav-Goel/Neural_Emotion_Intensity_Prediction 9 0 0 over 7 years ago 0 1 Jupyter Notebook
The code for our proposed neural models which give state-of-the-art performance for emotion intensity detection in tweets.
gaoxiangyu369/Identifying_Tweets_with_Adverse_Drug_Reactions 7 0 0 over 8 years ago 0 1 Python
Identifying Tweets with Adverse Drug Reactions.
malayyoub/emojis-to-train-emotion-classifiers 6 0 0 about 3 years ago 0 0 mit
This repository is for our work on the use of emojis to train emotion classifiers for Arabic tweets. It contains the dataset and the lexicons we created.
rsher60/Sentiment-Analysis-by-combining-Machine-Learning-and-Lexicon-Based-methods 6 0 0 over 7 years ago 0 1 Python
This project is on twitter sentimental analysis by combining lexicon based and machine learning approaches. A supervised lexicon-based approach for extracting sentiments from tweets was implemented. Various supervised machine learning approaches were tested using scikit-learn libraries in python and implemented Decision Trees and Naive Bayes techniques.
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