Detecting the public pulse is sub topic under sentiment analysis, but it is unique in terms of direction. In most cases of sentiment analysis any document will have positive and negative reviews a machine will train to predict the polarity of the new documents. The public pulse detection on a decision is multidimensional, every decision has multiple events and each event is having positive and negative reviews. Obtaining the final decision is a challenge. This article develops a deep learning model to predict the public pulse based on the CNAPR dataset. The model predicts more accurately and it is having a loss of 0.24.

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