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  • 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

    A Robust Model for Translating Arabic Sign Language into Spoken Arabic Using Deep Learning

    Khalid M. O. Nahar1, Ammar Almomani2,3,*, Nahlah Shatnawi1, Mohammad Alauthman4

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2037-2057, 2023, DOI:10.32604/iasc.2023.038235

    Abstract This study presents a novel and innovative approach to automatically translating Arabic Sign Language (ATSL) into spoken Arabic. The proposed solution utilizes a deep learning-based classification approach and the transfer learning technique to retrain 12 image recognition models. The image-based translation method maps sign language gestures to corresponding letters or words using distance measures and classification as a machine learning technique. The results show that the proposed model is more accurate and faster than traditional image-based models in classifying Arabic-language signs, with a translation accuracy of 93.7%. This research makes a significant contribution to the field of ATSL. It offers… More >

  • Open Access

    ARTICLE

    A PERT-BiLSTM-Att Model for Online Public Opinion Text Sentiment Analysis

    Mingyong Li, Zheng Jiang*, Zongwei Zhao, Longfei Ma

    Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2387-2406, 2023, DOI:10.32604/iasc.2023.037900

    Abstract As an essential category of public event management and control, sentiment analysis of online public opinion text plays a vital role in public opinion early warning, network rumor management, and netizens’ personality portraits under massive public opinion data. The traditional sentiment analysis model is not sensitive to the location information of words, it is difficult to solve the problem of polysemy, and the learning representation ability of long and short sentences is very different, which leads to the low accuracy of sentiment classification. This paper proposes a sentiment analysis model PERT-BiLSTM-Att for public opinion text based on the pre-training model… More >

  • Open Access

    ARTICLE

    Improved Metaheuristics with Deep Learning Enabled Movie Review Sentiment Analysis

    Abdelwahed Motwakel1,*, Najm Alotaibi2, Eatedal Alabdulkreem3, Hussain Alshahrani4, Mohamed Ahmed Elfaki4, Mohamed K Nour5, Radwa Marzouk6, Mahmoud Othman7

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1249-1266, 2023, DOI:10.32604/csse.2023.034227

    Abstract Sentiment Analysis (SA) of natural language text is not only a challenging process but also gains significance in various Natural Language Processing (NLP) applications. The SA is utilized in various applications, namely, education, to improve the learning and teaching processes, marketing strategies, customer trend predictions, and the stock market. Various researchers have applied lexicon-related approaches, Machine Learning (ML) techniques and so on to conduct the SA for multiple languages, for instance, English and Chinese. Due to the increased popularity of the Deep Learning models, the current study used diverse configuration settings of the Convolution Neural Network (CNN) model and conducted… More >

  • Open Access

    ARTICLE

    Web Intelligence with Enhanced Sunflower Optimization Algorithm for Sentiment Analysis

    Abeer D. Algarni*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1233-1247, 2023, DOI:10.32604/csse.2022.026915

    Abstract Exponential increase in the quantity of user generated content in websites and social networks have resulted in the emergence of web intelligence approaches. Several natural language processing (NLP) tools are commonly used to examine the large quantity of data generated online. Particularly, sentiment analysis (SA) is an effective way of classifying the data into different classes of user opinions or sentiments. The latest advances in machine learning (ML) and deep learning (DL) approaches offer an intelligent way of analyzing sentiments. In this view, this study introduces a web intelligence with enhanced sunflower optimization based deep learning model for sentiment analysis… More >

  • Open Access

    ARTICLE

    ESG Discourse Analysis Through BERTopic: Comparing News Articles and Academic Papers

    Haein Lee1, Seon Hong Lee1, Kyeo Re Lee2, Jang Hyun Kim3,*

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6023-6037, 2023, DOI:10.32604/cmc.2023.039104

    Abstract Environmental, social, and governance (ESG) factors are critical in achieving sustainability in business management and are used as values aiming to enhance corporate value. Recently, non-financial indicators have been considered as important for the actual valuation of corporations, thus analyzing natural language data related to ESG is essential. Several previous studies limited their focus to specific countries or have not used big data. Past methodologies are insufficient for obtaining potential insights into the best practices to leverage ESG. To address this problem, in this study, the authors used data from two platforms: LexisNexis, a platform that provides media monitoring, and… More >

  • Open Access

    ARTICLE

    Cyberbullying Detection and Recognition with Type Determination Based on Machine Learning

    Khalid M. O. Nahar1,*, Mohammad Alauthman2, Saud Yonbawi3, Ammar Almomani4,5

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5307-5319, 2023, DOI:10.32604/cmc.2023.031848

    Abstract Social media networks are becoming essential to our daily activities, and many issues are due to this great involvement in our lives. Cyberbullying is a social media network issue, a global crisis affecting the victims and society as a whole. It results from a misunderstanding regarding freedom of speech. In this work, we proposed a methodology for detecting such behaviors (bullying, harassment, and hate-related texts) using supervised machine learning algorithms (SVM, Naïve Bayes, Logistic regression, and random forest) and for predicting a topic associated with these text data using unsupervised natural language processing, such as latent Dirichlet allocation. In addition,… More >

  • Open Access

    ARTICLE

    SA-Model: Multi-Feature Fusion Poetic Sentiment Analysis Based on a Hybrid Word Vector Model

    Lingli Zhang1, Yadong Wu1,*, Qikai Chu2, Pan Li2, Guijuan Wang3,4, Weihan Zhang1, Yu Qiu1, Yi Li1

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 631-645, 2023, DOI:10.32604/cmes.2023.027179

    Abstract Sentiment analysis in Chinese classical poetry has become a prominent topic in historical and cultural tracing, ancient literature research, etc. However, the existing research on sentiment analysis is relatively small. It does not effectively solve the problems such as the weak feature extraction ability of poetry text, which leads to the low performance of the model on sentiment analysis for Chinese classical poetry. In this research, we offer the SA-Model, a poetic sentiment analysis model. SA-Model firstly extracts text vector information and fuses it through Bidirectional encoder representation from transformers-Whole word masking-extension (BERT-wwm-ext) and Enhanced representation through knowledge integration (ERNIE)… More >

  • Open Access

    ARTICLE

    Optimal Quad Channel Long Short-Term Memory Based Fake News Classification on English Corpus

    Manar Ahmed Hamza1,*, Hala J. Alshahrani2, Khaled Tarmissi3, Ayman Yafoz4, Amal S. Mehanna5, Ishfaq Yaseen1, Amgad Atta Abdelmageed1, Mohamed I. Eldesouki6

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3303-3319, 2023, DOI:10.32604/csse.2023.034823

    Abstract The term ‘corpus’ refers to a huge volume of structured datasets containing machine-readable texts. Such texts are generated in a natural communicative setting. The explosion of social media permitted individuals to spread data with minimal examination and filters freely. Due to this, the old problem of fake news has resurfaced. It has become an important concern due to its negative impact on the community. To manage the spread of fake news, automatic recognition approaches have been investigated earlier using Artificial Intelligence (AI) and Machine Learning (ML) techniques. To perform the medicinal text classification tasks, the ML approaches were applied, and… 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 >

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