Haein Lee¹, Seon Hong Lee¹, Kyeo Re Lee², Jang Hyun Kim^3,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6023-6037, 2023, DOI:10.32604/cmc.2023.039104 - 29 April 2023

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… More >

Khalid M. O. Nahar^1,*, Mohammad Alauthman², Saud Yonbawi³, Ammar Almomani^4,5

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5307-5319, 2023, DOI:10.32604/cmc.2023.031848 - 29 April 2023

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 More >

Lingli Zhang¹, Yadong Wu^1,*, Qikai Chu², Pan Li², Guijuan Wang^3,4, 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 - 23 April 2023

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 More >

Manar Ahmed Hamza^1,*, 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 - 03 April 2023

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… More >

Abdelwahed Motwakel^1,*, 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 - 03 April 2023

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… More >

Zhiping Liang^*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4519-4534, 2023, DOI:10.32604/cmc.2023.037035 - 31 March 2023

Abstract In view of the various adverse effects, fake news detection has become an extremely important task. So far, many detection methods have been proposed, but these methods still have some limitations. For example, only two independently encoded unimodal information are concatenated together, but not integrated with multimodal information to complete the complementary information, and to obtain the correlated information in the news content. This simple fusion approach may lead to the omission of some information and bring some interference to the model. To solve the above problems, this paper proposes the Fake News Detection model… More >

Huma Israr^1,*, Safdar Abbas Khan¹, Muhammad Ali Tahir¹, Muhammad Khuram Shahzad¹, Muneer Ahmad¹, Jasni Mohamad Zain^2,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2981-3009, 2023, DOI:10.32604/cmc.2023.035814 - 31 March 2023

Abstract In bilingual translation, attention-based Neural Machine Translation (NMT) models are used to achieve synchrony between input and output sequences and the notion of alignment. NMT model has obtained state-of-the-art performance for several language pairs. However, there has been little work exploring useful architectures for Urdu-to-English machine translation. We conducted extensive Urdu-to-English translation experiments using Long short-term memory (LSTM)/Bidirectional recurrent neural networks (Bi-RNN)/Statistical recurrent unit (SRU)/Gated recurrent unit (GRU)/Convolutional neural network (CNN) and Transformer. Experimental results show that Bi-RNN and LSTM with attention mechanism trained iteratively, with a scalable data set, make precise predictions on unseen… More >

Manar Ahmed Hamza^1,*, Hala J. Alshahrani², Abdulkhaleq Q. A. Hassan³, Abdulbaset Gaddah⁴, Nasser Allheeib⁵, Suleiman Ali Alsaif⁶, Badriyya B. Al-onazi⁷, Heba Mohsen⁸

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4137-4154, 2023, DOI:10.32604/cmc.2023.035237 - 31 March 2023

Abstract Computational linguistics refers to an interdisciplinary field associated with the computational modelling of natural language and studying appropriate computational methods for linguistic questions. The number of social media users has been increasing over the last few years, which have allured researchers’ interest in scrutinizing the new kind of creative language utilized on the Internet to explore communication and human opinions in a better way. Irony and sarcasm detection is a complex task in Natural Language Processing (NLP). Irony detection has inferences in advertising, sentiment analysis (SA), and opinion mining. For the last few years, irony-aware… More >

Yeferson Torres-Berru^1,2,*, Vivian F. Lopez-Batista¹, Lorena Conde Zhingre³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3501-3516, 2023, DOI:10.32604/iasc.2023.035367 - 15 March 2023

Abstract In a public procurement process, corruption can occur at each stage, favoring a participant with a previous agreement, which can result in over-pricing and purchases of substandard products, as well as gender discrimination. This paper’s aim is to detect biased purchases using a Spanish Language corpus, analyzing text from the questions and answers registry platform by applicants in a public procurement process in Ecuador. Additionally, gender bias is detected, promoting both men and women to participate under the same conditions. In order to detect gender bias and favoritism towards certain providers by contracting entities, the… More >

Manar Ahmed Hamza^1,*, Hala J. Alshahrani², Jaber S. Alzahrani³, Heba Mohsen⁴, Mohamed I. Eldesouki⁵, Mohammed Rizwanullah¹

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2619-2635, 2023, DOI:10.32604/csse.2023.034519 - 09 February 2023

Abstract Aspect-Based Sentiment Analysis (ABSA) on Arabic corpus has become an active research topic in recent days. ABSA refers to a fine-grained Sentiment Analysis (SA) task that focuses on the extraction of the conferred aspects and the identification of respective sentiment polarity from the provided text. Most of the prevailing Arabic ABSA techniques heavily depend upon dreary feature-engineering and pre-processing tasks and utilize external sources such as lexicons. In literature, concerning the Arabic language text analysis, the authors made use of regular Machine Learning (ML) techniques that rely on a group of rare sources and tools.… More >