• SRIRAM N

With the development of Internet and large amount of text data, it has been a very significant research to get vital information from text ocean. This paper promotes a RNN language model based on Long Short Term Memory (LSTM), which can get proper sequence information effectively. LSTM is better in analyzing long sentence emotions effectively compared with RNN model. LSTM is capable of learning long term capabilities. Remembering information for a long period of time is its natural. LSTM is a special kind of RNN. This paper aims at analyzing sentiments of US airlines with only two attribute positive and negative. Experiments show that LSTM can better in accuracy rate and recall rate than RNN.

rnn,lstm

"US AIRLINES SENTIMENT ANALYSIS USING LSTM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.78-81, April-2019, Available :http://www.jetir.org/papers/JETIR1904G70.pdf

"US AIRLINES SENTIMENT ANALYSIS USING LSTM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp78-81, April-2019, Available at : http://www.jetir.org/papers/JETIR1904G70.pdf