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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Ahmed T. Sadiq
University of Technology
Electrical & Electronics Engineering

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Analyzing sentiment system to specify polarity by lexicon-based Dhafar Hamed Abd; Ayad R. Abbas; Ahmed T. Sadiq
Bulletin of Electrical Engineering and Informatics Vol 10, No 1: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i1.2471

Abstract

Currently, sentiment analysis into positive or negative getting more attention from the researchers. With the rapid development of the internet and social media have made people express their views and opinion publicly. Analyzing the sentiment in people views and opinion impact many fields such as services and productions that companies offer. Movie reviewer needs many processing to be prepared to detect emotion, classify them and achieve high accuracy. The difficulties arise due of the structure and grammar of the language and manage the dictionary. We present a system that assigns scores indicating positive or negative opinion to each distinct entity in the text corpus. Propose an innovative formula to compute the polarity score for each word occurring in the text and find it in positive dictionary or negative dictionary we have to remove it from text. After classification, the words are stored in a list that will be used to calculate the accuracy. The results reveal that the system achieved the best results in accuracy of 76.585%.
Healthcare assessment for beauty centers using hybrid sentiment analysis Abeer Khalid Al-Mashhadany; Ahmed T. Sadiq; Sura Mazin Ali; Amjed Abbas Ahmed
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp890-897

Abstract

Because of COVID-19, healthcare became the first interesting domain at the world. Here, comes the role of researchers to do what they can to guide people. Nowadays, the most wanted field is beauty industry. It achieved large market. And the estimation is toward the growing. Researchers can give advice to prevent unhealthy causes in this field. They can apply sentiment analysis methods to make decision whether a Beauty center is healthy or unhealthy. This work develops an improved method of sentiment analysis to classify the beauty centers in Iraq into healthy and unhealthy classes. Researchers used comments of beauty centers’ Facebooks to perform the assessment. The methodologies encompass the two approaches lexicon-based and machine-learning-based. Three machine learning mechanisms had been applied; rough set theory, naïve bayes, and k-nearest neighbors. It will be shown that rough set theory is the best compared with the others two. Rough set theory achieved 95.2%, while Naïve Bayes achieved 87.5% and k-nearest neighbors achieved 78%.
Co-Authors Abeer Khalid Al-Mashhadany Amjed Abbas Ahmed Ayad R. Abbas Dhafar Hamed Abd Sura Mazin Ali