SA-using-SMOTE-and-Stacking-deep-learning-model

Sentiment Analysis of Imbalanced Dataset using SMOTE

The Sentiment Analysis of Imbalanced Datasets (in English, Arabic, and Moroccan Dialect) using SMOTE is novel method based on BERT embedding (for each language) and stacked deep learning algorithms, namely: LSTM, BiLSTM, GRU, and CNN that provide state-of-the-art results on the imbalanced dialect dataset in terms of accuracy.

Datasets

We used three datasets in English, Arabic, and Moroccan Dialect as shown in the following table:

Language	Dataset	positive	negative
English	Reviews	27411	8189
Arabic	Arabic_tweets	835	1253
Moroccan Dialect	dataset	14628	24932

Python comparability

This code is compatible with python 3.x. If python 3 is not default in your system, please using python3 and pip3 commands instead of python and pip commands.