Predicting Human Behavior Using Arabic Sentiment Analysis on Social Media: Approaches and Challenges
عبده, ., عبد الجابر, ., فرحان, ., عثمان, . (2024). Predicting Human Behavior Using Arabic Sentiment Analysis on Social Media: Approaches and Challenges. EKB Journal Management System, 6(1), 22-33. doi: 10.21608/fcihib.2023.201708.1084
محمد عبده; سيد عبد الجابر; مروة صلاح فرحان; نرمين عثمان. "Predicting Human Behavior Using Arabic Sentiment Analysis on Social Media: Approaches and Challenges". EKB Journal Management System, 6, 1, 2024, 22-33. doi: 10.21608/fcihib.2023.201708.1084
عبده, ., عبد الجابر, ., فرحان, ., عثمان, . (2024). 'Predicting Human Behavior Using Arabic Sentiment Analysis on Social Media: Approaches and Challenges', EKB Journal Management System, 6(1), pp. 22-33. doi: 10.21608/fcihib.2023.201708.1084
عبده, ., عبد الجابر, ., فرحان, ., عثمان, . Predicting Human Behavior Using Arabic Sentiment Analysis on Social Media: Approaches and Challenges. EKB Journal Management System, 2024; 6(1): 22-33. doi: 10.21608/fcihib.2023.201708.1084

Predicting Human Behavior Using Arabic Sentiment Analysis on Social Media: Approaches and Challenges

النشرة المعلوماتية في الحاسبات والمعلومات
Volume 6, Issue 1 - Serial Number 20240601, January 2024, Page 22-33  XML PDF (997.32 K)
Document Type: المقالة الأصلية
DOI: 10.21608/fcihib.2023.201708.1084
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Authors
محمد عبده email orcid 1; سيد عبد الجابرorcid 1; مروة صلاح فرحانorcid 1, 2; نرمين عثمانorcid 1, 2
1قسم نظم المعلومات ، كلية الحاسبات والذكاء الاصطناعي ، جامعة حلوان ، القاهرة ، مصر
2كلية المعلوماتية وعلوم الحاسب، الجامعة البريطانية في مصر، القاهرة، مصر
Abstract
The rapid growth of social networking and micro-blogging websites has motivated researchers to analyze published content to identify and predict human behavior. With the ongoing growth in data volume, the efficient and effective extraction of valuable information has become crucial. Researchers are tackling this problem using big data analytics. However, most studies have focused on the English language and fewer research efforts have been devoted to the Arabic language. This paper covers the recent Arabic sentiment analysis research, highlighting the most important studies that analyzed content from social media to predict human behavior and the different approaches used. Sentiment analysis studies varied between lexicon-based, traditional machine learning-based, deep learning, and hybrid approaches, in addition to employing swarm intelligence to optimize the performance of text classification algorithms. The reviews showed that Naïve Bayes (NB) and Support Vector Machine (SVM) were the most widely used algorithms among traditional machine learning algorithms. The results also showed that using deep learning approaches achieves better accuracy than other approaches. Also, the use of optimization algorithms based on swarm intelligence had a significant impact on increasing the accuracy of text clustering.
 

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Keywords
Sentiment Analysis; Human Behavior; Machine Learning; Natural Language Processing; Deep Learning
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