Sentiment analysis on product reviews data using supervised learning
Wedjdane Nahili, Khaled Rezeg, Okba Kazar · 2020
With the availability of text data in various forms on social media platforms, text mining and sentiment analysis have received huge attention. The task of deriving information from this volume of data in order 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 labelling, 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.CCS Concepts