Big Data Analytics using Supervised Learning: A Comprehensive Review of Recent Techniques
Wedjdane Nahili · International Journal for Research in Applied Science and Engineering Technology · 2020
With the availability of text data in various forms on social media platforms, text mining, and sentiment analysis has received huge attention. The task of deriving information from this volume of data to extract knowledge is very complex and expensive because it is usually unstructured and contains noise.Recently, there is a growing need for implementing various approaches and models for efficiently processing this type of data and extracting useful information.This process is known as sentiment analysis, which includes: data gathering, data pre-processing, feature engineering and labeling, finally the application of various natural language processing and machine learning algorithms.This paper provides an overview of the most recent methods used in text mining and sentiment analysis along with their detailed description and a discussion of obtained results.