Analysis of Twitter Data Using Deep Learning Approach: LSTM

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Vikas Malik, Amit Kumar

Abstract

Sentiment analysis the procedure of computationally identifying and categorizing evaluations expressed in a chunk of text, especially with a view to decide whether the writer’s mind-set toward a selected subject matter, product, etc. is high-quality, poor, or impartial[1]. Now a days the growth of social websites, running a blog offerings and electronic media con-tributes big amount of consumer supply messages which includes customer reviews, remarks and evaluations. Sentiment evaluation is an important term cited gather facts in a source with the aid of the usage of NLP, computational[2] linguistics and text analysis and to make decision through subjective information extracting and analyzing opinion, figuring out advantageous and bad opinions measuring how definitely and negatively an entity (public ,organization, product) is concerned. in the beyond decade , researcher have performed the sentiment analysis using device getting to know techniques which include guide vector gadget, naive bayes , maximum entropy method etc. Sentient analysis on social media textual content received lot of recognition because it includes pointers and pointers. lately deep gaining knowledge of methods like long short-term memory (LSTM) and convolution neural network (CNN) have gained recognition by means of displaying promising effects for speech and photograph processing, obligations in NLP through learning functions wealthy deep illustration from the facts robotically.

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How to Cite
, V. M. A. K. “Analysis of Twitter Data Using Deep Learning Approach: LSTM”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 6, no. 4, Apr. 2018, pp. 144-9, doi:10.17762/ijritcc.v6i4.1534.
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