Dhiaa Musleh¹, Atta Rahman^1,*, Mohammed Abbas Alkherallah¹, Menhal Kamel Al-Bohassan¹, Mustafa Mohammed Alawami¹, Hayder Ali Alsebaa¹, Jawad Ali Alnemer¹, Ghazi Fayez Al-Mutairi¹, May Issa Aldossary², Dalal A. Aldowaihi¹, Fahd Alhaidari³

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1033-1054, 2024, DOI:10.32604/cmc.2024.048003

Abstract With the rapid growth of internet usage, a new situation has been created that enables practicing bullying. Cyberbullying has increased over the past decade, and it has the same adverse effects as face-to-face bullying, like anger, sadness, anxiety, and fear. With the anonymity people get on the internet, they tend to be more aggressive and express their emotions freely without considering the effects, which can be a reason for the increase in cyberbullying and it is the main motive behind the current study. This study presents a thorough background of cyberbullying and the techniques used… More >

Badriyya B. Al-onazi¹, Abdulkhaleq Q. A. Hassan², Mohamed K. Nour³, Mesfer Al Duhayyim^4,*, Abdullah Mohamed⁵, Amgad Atta Abdelmageed⁶, Ishfaq Yaseen⁶, Gouse Pasha Mohammed⁶

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2575-2591, 2023, DOI:10.32604/cmc.2023.033531

Abstract Sentiment Analysis (SA), a Machine Learning (ML) technique, is often applied in the literature. The SA technique is specifically applied to the data collected from social media sites. The research studies conducted earlier upon the SA of the tweets were mostly aimed at automating the feature extraction process. In this background, the current study introduces a novel method called Quantum Particle Swarm Optimization with Deep Learning-Based Sentiment Analysis on Arabic Tweets (QPSODL-SAAT). The presented QPSODL-SAAT model determines and classifies the sentiments of the tweets written in Arabic. Initially, the data pre-processing is performed to convert… More >

Aisha M. Mashraqi, Hanan T. Halawani^*

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2555-2570, 2023, DOI:10.32604/csse.2023.031246

Abstract Sentiment Analysis (SA) is one of the Machine Learning (ML) techniques that has been investigated by several researchers in recent years, especially due to the evolution of novel data collection methods focused on social media. In literature, it has been reported that SA data is created for English language in excess of any other language. It is challenging to perform SA for Arabic Twitter data owing to informal nature and rich morphology of Arabic language. An earlier study conducted upon SA for Arabic Twitter focused mostly on automatic extraction of the features from the text.… More >

Abeer A. AlFutamani, Heyam H. Al-Baity^*

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 89-109, 2021, DOI:10.32604/iasc.2021.016555

Abstract Social media sites produce a large amount of data and offer a highly competitive advantage for companies when they can benefit from and address data, as data provides a deeper understanding of clients and their needs. This understanding of clients helps in effectively making the correct decisions within the company, based on data obtained from social media websites. Thus, sentiment analysis has become a key tool for understanding that data. Sentiment analysis is a research area that focuses on analyzing people’s emotions and opinions to identify the polarity (e.g., positive or negative) of a given… More >