Sentiment Analysis in Social Media using Machine Learning Techniques

  • Hayder A. Alatabi Computer Science Department, University of Technology, Baghdad, Iraq
  • Ayad R. Abbas Computer Science Department, University of Technology, Baghdad, Iraq
Keywords: Sentiment Analysis, Opinion Mining, Sentiment Mining, Social Media

Abstract

Over the last period, social media achieved a widespread use worldwide where the statistics indicate that more than three billion people are on social media, leading to large quantities of data online. To analyze these large quantities of data, a special classification method known as sentiment analysis, is used. This paper presents a new sentiment analysis system based on machine learning techniques, which aims to create a process to extract the polarity from social media texts. By using machine learning techniques, sentiment analysis achieved a great success around the world. This paper investigates this topic and proposes a sentiment analysis system built on Bayesian Rough Decision Tree (BRDT) algorithm. The experimental results show the success of this system where the accuracy of the system is more than 95% on social media data.

Published
2020-01-27
How to Cite
Alatabi, H. A., & Abbas, A. R. (2020). Sentiment Analysis in Social Media using Machine Learning Techniques. Iraqi Journal of Science, 61(1), 193-201. https://doi.org/10.24996/ijs.2020.61.1.22
Section
Computer Science

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