A Review on Data Driven Machine Learning Models for Sentiment Analysis

A Review on Data Driven Machine Learning Models for Sentiment Analysis

Archana Parihar1, Prof. Pankaj Raghuwanshi2

Abstract: Opinion Mining and sentiment analysis of big data has been seen as an active area of research lately. It has a wide range of applications in information systems, including classifying reviews, summarizing review and other real time applications. There are promising possibilities to use sentiment analysis in real time business models. The present work focuses on sentient analysis by classification of tweets from social media (twitter) data. Since the data sets are often extremely large and complex, hence off late, opinion mining and sentiment analysis is executed based on artificial intelligence and machine learning models. This paper presents a systematic review of the existing methods for sentiment analysis of social media data along with their salient contribution.

Keywords: Data Mining, Opinion Mining, Sentiment Analysis, Machine Learning, Classification Accuracy.