A Novel Random Forest Implementation of Sentiment Analysis

EasyChair Preprint 3507

Abstract

In today’s world, we humans have been communicating with each other through calls, social media applications like WhatsApp, Facebook, Twitter, etc. From the social media apps, we get social media data from those applications and check what sentences are positive and negative sentiment using sentiment analysis and using deep learning methods like deep neural networks for classifying them under positive or negative sentiment polarity from twitter accounts. The data that we get from these social sites are being used for many social problems and used in government to analyze the opinion about social media users. This technique is called sentiment analysis. The main purpose of this sentiment analysis for this project will be to comparatively determine the writings made by user and check if they are going towards positive or negative. Only one technique will be used her – Machine Learning Algorithms –Random Forest. This paper uses the machine learning algorithm-Random Forest. The scope of this project will be widely used in classifying the text in terms of positive and negative polarity and help the government to handle social and threats due to the text classification

Keyphrases: NLTK, Random Forest, Sentiment Analysis

@booklet{EasyChair:3507,
  author    = {Arnav Munshi and Sanchit Sapra and M Arvindhan},
  title     = {A Novel Random Forest Implementation of Sentiment Analysis},
  howpublished = {EasyChair Preprint 3507},
  year      = {EasyChair, 2020}}