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  • Open Access

    ARTICLE

    An Adaptive Hate Speech Detection Approach Using Neutrosophic Neural Networks for Social Media Forensics

    Yasmine M. Ibrahim1,2, Reem Essameldin3, Saad M. Darwish1,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 243-262, 2024, DOI:10.32604/cmc.2024.047840

    Abstract Detecting hate speech automatically in social media forensics has emerged as a highly challenging task due to the complex nature of language used in such platforms. Currently, several methods exist for classifying hate speech, but they still suffer from ambiguity when differentiating between hateful and offensive content and they also lack accuracy. The work suggested in this paper uses a combination of the Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO) to adjust the weights of two Multi-Layer Perceptron (MLPs) for neutrosophic sets classification. During the training process of the MLP, the WOA is employed to explore and determine… More >

  • Open Access

    ARTICLE

    Improved Attentive Recurrent Network for Applied Linguistics-Based Offensive Speech Detection

    Manar Ahmed Hamza1,*, Hala J. Alshahrani2, Khaled Tarmissi3, Ayman Yafoz4, Amira Sayed A. Aziz5, Mohammad Mahzari6, Abu Sarwar Zamani1, Ishfaq Yaseen1

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1691-1707, 2023, DOI:10.32604/csse.2023.034798

    Abstract Applied linguistics is one of the fields in the linguistics domain and deals with the practical applications of the language studies such as speech processing, language teaching, translation and speech therapy. The ever-growing Online Social Networks (OSNs) experience a vital issue to confront, i.e., hate speech. Amongst the OSN-oriented security problems, the usage of offensive language is the most important threat that is prevalently found across the Internet. Based on the group targeted, the offensive language varies in terms of adult content, hate speech, racism, cyberbullying, abuse, trolling and profanity. Amongst these, hate speech is the most intimidating form of… More >

  • Open Access

    ARTICLE

    Improved Ant Lion Optimizer with Deep Learning Driven Arabic Hate Speech Detection

    Abdelwahed Motwakel1,*, Badriyya B. Al-onazi2, Jaber S. Alzahrani3, Sana Alazwari4, Mahmoud Othman5, Abu Sarwar Zamani1, Ishfaq Yaseen1, Amgad Atta Abdelmageed1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3321-3338, 2023, DOI:10.32604/csse.2023.033901

    Abstract Arabic is the world’s first language, categorized by its rich and complicated grammatical formats. Furthermore, the Arabic morphology can be perplexing because nearly 10,000 roots and 900 patterns were the basis for verbs and nouns. The Arabic language consists of distinct variations utilized in a community and particular situations. Social media sites are a medium for expressing opinions and social phenomena like racism, hatred, offensive language, and all kinds of verbal violence. Such conduct does not impact particular nations, communities, or groups only, extending beyond such areas into people’s everyday lives. This study introduces an Improved Ant Lion Optimizer with… More >

  • Open Access

    REVIEW

    A Review of Machine Learning Techniques in Cyberbullying Detection

    Daniyar Sultan1,2,*, Batyrkhan Omarov3, Zhazira Kozhamkulova4, Gulnur Kazbekova5, Laura Alimzhanova1, Aigul Dautbayeva6, Yernar Zholdassov1, Rustam Abdrakhmanov3

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5625-5640, 2023, DOI:10.32604/cmc.2023.033682

    Abstract Automatic identification of cyberbullying is a problem that is gaining traction, especially in the Machine Learning areas. Not only is it complicated, but it has also become a pressing necessity, considering how social media has become an integral part of adolescents’ lives and how serious the impacts of cyberbullying and online harassment can be, particularly among teenagers. This paper contains a systematic literature review of modern strategies, machine learning methods, and technical means for detecting cyberbullying and the aggressive command of an individual in the information space of the Internet. We undertake an in-depth review of 13 papers from four… More >

  • Open Access

    ARTICLE

    Cyberbullying-related Hate Speech Detection Using Shallow-to-deep Learning

    Daniyar Sultan1,2, Aigerim Toktarova3,*, Ainur Zhumadillayeva4, Sapargali Aldeshov5,6, Shynar Mussiraliyeva1, Gulbakhram Beissenova6,7, Abay Tursynbayev8, Gulmira Baenova4, Aigul Imanbayeva6

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2115-2131, 2023, DOI:10.32604/cmc.2023.032993

    Abstract Communication in society had developed within cultural and geographical boundaries prior to the invention of digital technology. The latest advancements in communication technology have significantly surpassed the conventional constraints for communication with regards to time and location. These new platforms have ushered in a new age of user-generated content, online chats, social network and comprehensive data on individual behavior. However, the abuse of communication software such as social media websites, online communities, and chats has resulted in a new kind of online hostility and aggressive actions. Due to widespread use of the social networking platforms and technological gadgets, conventional bullying… More >

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