Previous research on emotion recognition of Twitter users centered on the use of lexicons and basic classifiers on pack
of words models, despite the recent accomplishments of deep learning in many disciplines of natural language processing. The
study's main question is if deep learning can help them improve their performance. Because of the scant contextual information
that most posts offer, emotion analysis is still difficult. The suggested method can capture more emotion sematic than existing
models by projecting emoticons and words into emoticon space, which improves the performance of emotion analysis.
