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  • Open Access

    ARTICLE

    Applying English Idiomatic Expressions to Classify Deep Sentiments in COVID-19 Tweets

    Bashar Tahayna, Ramesh Kumar Ayyasamy*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 37-54, 2023, DOI:10.32604/csse.2023.036648

    Abstract Millions of people are connecting and exchanging information on social media platforms, where interpersonal interactions are constantly being shared. However, due to inaccurate or misleading information about the COVID-19 pandemic, social media platforms became the scene of tense debates between believers and doubters. Healthcare professionals and public health agencies also use social media to inform the public about COVID-19 news and updates. However, they occasionally have trouble managing massive pandemic-related rumors and frauds. One reason is that people share and engage, regardless of the information source, by assuming the content is unquestionably true. On Twitter, users use words and phrases… 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

    CBOE Volatility Index Forecasting under COVID-19: An Integrated BiLSTM-ARIMA-GARCH Model

    Min Hyung Park1, Dongyan Nan2,3, Yerin Kim1, Jang Hyun Kim1,2,3,*

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 121-134, 2023, DOI:10.32604/csse.2023.033247

    Abstract After the outbreak of COVID-19, the global economy entered a deep freeze. This observation is supported by the Volatility Index (VIX), which reflects the market risk expected by investors. In the current study, we predicted the VIX using variables obtained from the sentiment analysis of data on Twitter posts related to the keyword “COVID-19,” using a model integrating the bidirectional long-term memory (BiLSTM), autoregressive integrated moving average (ARIMA) algorithm, and generalized autoregressive conditional heteroskedasticity (GARCH) model. The Linguistic Inquiry and Word Count (LIWC) program and Valence Aware Dictionary for Sentiment Reasoning (VADER) model were utilized as sentiment analysis methods. The… 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

    Text Sentiment Analysis Based on Multi-Layer Bi-Directional LSTM with a Trapezoidal Structure

    Zhengfang He1,2,*, Cristina E. Dumdumaya2, Ivy Kim D. Machica2

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 639-654, 2023, DOI:10.32604/iasc.2023.035352

    Abstract Sentiment analysis, commonly called opinion mining or emotion artificial intelligence (AI), employs biometrics, computational linguistics, natural language processing, and text analysis to systematically identify, extract, measure, and investigate affective states and subjective data. Sentiment analysis algorithms include emotion lexicon, traditional machine learning, and deep learning. In the text sentiment analysis algorithm based on a neural network, multi-layer Bi-directional long short-term memory (LSTM) is widely used, but the parameter amount of this model is too huge. Hence, this paper proposes a Bi-directional LSTM with a trapezoidal structure model. The design of the trapezoidal structure is derived from classic neural networks, such… More >

  • Open Access

    ARTICLE

    Modified Sine Cosine Optimization with Adaptive Deep Belief Network for Movie Review Classification

    Hala J. Alshahrani1, Abdulbaset Gaddah2, Ehab S. Alnuzaili3, Mesfer Al Duhayyim4,*, Heba Mohsen5, Ishfaq Yaseen6, Amgad Atta Abdelmageed6, Gouse Pasha Mohammed6

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 283-300, 2023, DOI:10.32604/iasc.2023.035334

    Abstract Sentiment analysis (SA) is a growing field at the intersection of computer science and computational linguistics that endeavors to automatically identify the sentiment presented in text. Computational linguistics aims to describe the fundamental methods utilized in the formation of computer methods for understanding natural language. Sentiment is classified as a negative or positive assessment articulated through language. SA can be commonly used for the movie review classification that involves the automatic determination that a review posted online (of a movie) can be negative or positive toward the thing that has been reviewed. Deep learning (DL) is becoming a powerful machine… More >

  • Open Access

    ARTICLE

    Improving Targeted Multimodal Sentiment Classification with Semantic Description of Images

    Jieyu An*, Wan Mohd Nazmee Wan Zainon, Zhang Hao

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5801-5815, 2023, DOI:10.32604/cmc.2023.038220

    Abstract Targeted multimodal sentiment classification (TMSC) aims to identify the sentiment polarity of a target mentioned in a multimodal post. The majority of current studies on this task focus on mapping the image and the text to a high-dimensional space in order to obtain and fuse implicit representations, ignoring the rich semantic information contained in the images and not taking into account the contribution of the visual modality in the multimodal fusion representation, which can potentially influence the results of TMSC tasks. This paper proposes a general model for Improving Targeted Multimodal Sentiment Classification with Semantic Description of Images (ITMSC) as… More >

  • Open Access

    ARTICLE

    Sine Cosine Optimization with Deep Learning-Based Applied Linguistics for Sentiment Analysis on COVID-19 Tweets

    Abdelwahed Motwakel1,*, Hala J. Alshahrani2, Abdulkhaleq Q. A. Hassan3, Khaled Tarmissi4, Amal S. Mehanna5, Ishfaq Yaseen1, Amgad Atta Abdelmageed1, Mohammad Mahzari6

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 4767-4783, 2023, DOI:10.32604/cmc.2023.034840

    Abstract Applied linguistics is an interdisciplinary domain which identifies, investigates, and offers solutions to language-related real-life problems. The new coronavirus disease, otherwise known as Coronavirus disease (COVID-19), has severely affected the everyday life of people all over the world. Specifically, since there is insufficient access to vaccines and no straight or reliable treatment for coronavirus infection, the country has initiated the appropriate preventive measures (like lockdown, physical separation, and masking) for combating this extremely transmittable disease. So, individuals spent more time on online social media platforms (i.e., Twitter, Facebook, Instagram, LinkedIn, and Reddit) and expressed their thoughts and feelings about coronavirus… 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

    An Ensemble-Based Hotel Reviews System Using Naive Bayes Classifier

    Joseph Bamidele Awotunde1, Sanjay Misra2,*, Vikash Katta2, Oluwafemi Charles Adebayo1

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 131-154, 2023, DOI:10.32604/cmes.2023.026812

    Abstract The task of classifying opinions conveyed in any form of text online is referred to as sentiment analysis. The emergence of social media usage and its spread has given room for sentiment analysis in our daily lives. Social media applications and websites have become the foremost spring of data recycled for reviews for sentimentality in various fields. Various subject matter can be encountered on social media platforms, such as movie product reviews, consumer opinions, and testimonies, among others, which can be used for sentiment analysis. The rapid uncovering of these web contents contains divergence of many benefits like profit-making, which… More >

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