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Search Results (5)
  • Open Access

    ARTICLE

    Artificial Intelligence Based Sentence Level Sentiment Analysis of COVID-19

    Sundas Rukhsar1, Mazhar Javed Awan1, Usman Naseem2, Dilovan Asaad Zebari3, Mazin Abed Mohammed4,*, Marwan Ali Albahar5, Mohammed Thanoon5, Amena Mahmoud6

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 791-807, 2023, DOI:10.32604/csse.2023.038384

    Abstract Web-blogging sites such as Twitter and Facebook are heavily influenced by emotions, sentiments, and data in the modern era. Twitter, a widely used microblogging site where individuals share their thoughts in the form of tweets, has become a major source for sentiment analysis. In recent years, there has been a significant increase in demand for sentiment analysis to identify and classify opinions or expressions in text or tweets. Opinions or expressions of people about a particular topic, situation, person, or product can be identified from sentences and divided into three categories: positive for good, negative for bad, and neutral for… More >

  • Open Access

    ARTICLE

    Automatic Sentimental Analysis by Firefly with Levy and Multilayer Perceptron

    D. Elangovan1,*, V. Subedha2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2797-2808, 2023, DOI:10.32604/csse.2023.031988

    Abstract The field of sentiment analysis (SA) has grown in tandem with the aid of social networking platforms to exchange opinions and ideas. Many people share their views and ideas around the world through social media like Facebook and Twitter. The goal of opinion mining, commonly referred to as sentiment analysis, is to categorise and forecast a target’s opinion. Depending on if they provide a positive or negative perspective on a given topic, text documents or sentences can be classified. When compared to sentiment analysis, text categorization may appear to be a simple process, but number of challenges have prompted numerous… More >

  • Open Access

    ARTICLE

    Topic Modelling and Sentimental Analysis of Students’ Reviews

    Omer S. Alkhnbashi1, Rasheed Mohammad Nassr2,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6835-6848, 2023, DOI:10.32604/cmc.2023.034987

    Abstract Globally, educational institutions have reported a dramatic shift to online learning in an effort to contain the COVID-19 pandemic. The fundamental concern has been the continuance of education. As a result, several novel solutions have been developed to address technical and pedagogical issues. However, these were not the only difficulties that students faced. The implemented solutions involved the operation of the educational process with less regard for students’ changing circumstances, which obliged them to study from home. Students should be asked to provide a full list of their concerns. As a result, student reflections, including those from Saudi Arabia, have… More >

  • Open Access

    ARTICLE

    Deep Learning with Natural Language Processing Enabled Sentimental Analysis on Sarcasm Classification

    Abdul Rahaman Wahab Sait1,*, Mohamad Khairi Ishak2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2553-2567, 2023, DOI:10.32604/csse.2023.029603

    Abstract Sentiment analysis (SA) is the procedure of recognizing the emotions related to the data that exist in social networking. The existence of sarcasm in textual data is a major challenge in the efficiency of the SA. Earlier works on sarcasm detection on text utilize lexical as well as pragmatic cues namely interjection, punctuations, and sentiment shift that are vital indicators of sarcasm. With the advent of deep-learning, recent works, leveraging neural networks in learning lexical and contextual features, removing the need for handcrafted feature. In this aspect, this study designs a deep learning with natural language processing enabled SA (DLNLP-SA)… More >

  • Open Access

    ARTICLE

    Understand Students Feedback Using Bi-Integrated CRF Model Based Target Extraction

    K. Sangeetha1,*, D. Prabha2

    Computer Systems Science and Engineering, Vol.40, No.2, pp. 735-747, 2022, DOI:10.32604/csse.2022.019310

    Abstract Educational institutions showing interest to find the opinion of the students about their course and the instructors to enhance the teaching-learning process. For this, most research uses sentiment analysis to track students’ behavior. Traditional sentence-level sentiment analysis focuses on the whole sentence sentiment. Previous studies show that the sentiments alone are not enough to observe the feeling of the students because different words express different sentiments in a sentence. There is a need to extract the targets in a given sentence which helps to find the sentiment towards those targets. Target extraction is the subtask of targeted sentiment analysis. In… More >

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