  Text is the major method that is used for communication now a days, each and
every day lots of text are created. In this paper the text data is used for the
classification of the emotions. Emotions are the way of expression of the
persons feelings which has an high influence on the decision making tasks.
Datasets are collected which are available publically and combined together
based on the three emotions that are considered here positive, negative and
neutral. In this paper we have proposed the text representation method TFIDF
and keras embedding and then given to the classical machine learning algorithms
of which Logistics Regression gives the highest accuracy of about 75.6%, after
which it is passed to the deep learning algorithm which is the CNN which gives
the state of art accuracy of about 45.25%. For the research purpose the
datasets that has been collected are released.
