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A Survey on Classification Techniques for Opinion Mining and Sentiment Analysis - 2019

A Survey On Classification Techniques For Opinion Mining And Sentiment Analysis

Survey Paper On Classification Techniques For Opinion Mining And Sentiment Analysis

Research Area:  Machine Learning


Opinion mining is considered as a subfield of natural language processing, information retrieval and text mining. Opinion mining is the process of extracting human thoughts and perceptions from unstructured texts, which with regard to the emergence of online social media and mass volume of users’ comments, has become to a useful, attractive and also challenging issue. There are varieties of researches with different trends and approaches in this area, but the lack of a comprehensive study to investigate them from all aspects is tangible. In this paper we represent a complete, multilateral and systematic review of opinion mining and sentiment analysis to classify available methods and compare their advantages and drawbacks, in order to have better understanding of available challenges and solutions to clarify the future direction. For this purpose, we present a proper framework of opinion mining accompanying with its steps and levels and then we completely monitor, classify, summarize and compare proposed techniques for aspect extraction, opinion classification, summary production and evaluation, based on the major validated scientific works. In order to have a better comparison, we also propose some factors in each category, which help to have a better understanding of advantages and disadvantages of different methods.

Classification Techniques
Opinion Mining
Sentiment Analysis
Machine Learning
Deep Learning

Author(s) Name:  Fatemeh Hemmatian & Mohammad Karim Sohrabi

Journal name:  Artificial Intelligence Review

Conferrence name:  

Publisher name:  Springer

DOI:  10.1007/s10462-017-9599-6

Volume Information:  volume 52, pages: 1495–1545 (2019)