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Multi-class sentiment analysis problem to classify texts into six emotion categories: joy, sadness, anger, fear, surprise and love. It involves different text classification techniques. This includes dataset preparation, preprocessing, vectorization, training and prediction.
Since we tried a lot of combinations of word vectorization methods and classification algorithms the best results were given with the combination of support vector classifier and word2vec embeddings with accuracy of nearly 60%.