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All Journal Bulletin of Electrical Engineering and Informatics
Ahmed Hussein Ali
Al-Salam University College Computer Science Department Baghdad
Electrical & Electronics Engineering

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A real-time big data sentiment analysis for iraqi tweets using spark streaming Nashwan Dheyaa Zaki; Nada Yousif Hashim; Yasmin Makki Mohialden; Mostafa Abdulghafoor Mohammed; Tole Sutikno; Ahmed Hussein Ali
Bulletin of Electrical Engineering and Informatics Vol 9, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (692.543 KB) | DOI: 10.11591/eei.v9i4.1897

Abstract

The scale of data streaming in social networks, such as Twitter, is increasing exponentially. Twitter is one of the most important and suitable big data sources for machine learning research in terms of analysis, prediction, extract knowledge, and opinions. People use Twitter platform daily to express their opinion which is a fundamental fact that influence their behaviors. In recent years, the flow of Iraqi dialect has been increased, especially on the Twitter platform. Sentiment analysis for different dialects and opinion mining has become a hot topic in data science researches. In this paper, we will attempt to develop a real-time analytic model for sentiment analysis and opinion mining to Iraqi tweets using spark streaming, also create a dataset for researcher in this field. The Twitter handle Bassam AlRawi is the case study here. The new method is more suitable in the current day machine learning applications and fast online prediction. 
Co-Authors Mostafa Abdulghafoor Mohammed Nada Yousif Hashim Nashwan Dheyaa Zaki Tole Sutikno Yasmin Makki Mohialden