Sentiment Analysis of Urdu Language on different Social Media Platforms using Word2vec and LSTM
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Abstract
Sentiment analysis is the process to analyze the opinions, emotions or sentiments regarding a
review, comment, organization, firms or some event etc. with the introduction of social media
people tend to share their sentiments, opinions, emotions and ideas through them. Urdu which is
a dominant language in Indian sub-content. Most of people tend to share their sentiments using
Urdu as one of main language on these social media sites. In this paper the Urdu text available
on different social media platformswill be distributed into their vector forms by using the
Word2vec model and Long Short-Term Memory Units will be utilized for text classification and
SoftMaxfunction will be used as an activation function in LSTM. This SoftMax function has
been used for creating sentence polarity of positive, negative or neutral attribute. In this research
work the whole process has been used with recurrent Neural network.
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