Badriyya B. Al-onazi¹, Najm Alotaibi², Jaber S. Alzahrani³, Hussain Alshahrani⁴, Mohamed Ahmed Elfaki⁴, Radwa Marzouk⁵, Mahmoud Othman⁶, Abdelwahed Motwakel^7,*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1537-1554, 2023, DOI:10.32604/cmc.2023.034196

Abstract Text classification or categorization is the procedure of automatically tagging a textual document with most related labels or classes. When the number of labels is limited to one, the task becomes single-label text categorization. The Arabic texts include unstructured information also like English texts, and that is understandable for machine learning (ML) techniques, the text is changed and demonstrated by numerical value. In recent times, the dominant method for natural language processing (NLP) tasks is recurrent neural network (RNN), in general, long short term memory (LSTM) and convolutional neural network (CNN). Deep learning (DL) models are currently presented for deriving… More >

Yun-Jung Choi¹, Youn-Joo Um^2,*

International Journal of Mental Health Promotion, Vol.25, No.3, pp. 421-431, 2023, DOI:10.32604/ijmhp.2023.023255

Abstract Major media outlets have run many articles on the COVID-19 pandemic. Since the public suffers cognitive and emotional effects related to COVID-19 from such reports, we analyzed and reviewed the topics of news reports. We searched newspaper articles with the term ‘COVID-19’ term in four Korean daily newspapers from January 20, 2020, when the first patient in Korea was found, to June 15, 2020. Topic modeling analysis was conducted through text mining using R. Five themes were found: “Changes in people’s everyday life,” “Socio-economic shock,” “Trends in infection,” “Role of the government and business,” and “Increased psychological anxiety,” which all… More >

Eun-Joo Choi¹, Yun-Jung Choi^2,*

International Journal of Mental Health Promotion, Vol.25, No.1, pp. 21-29, 2023, DOI:10.32604/ijmhp.2022.022641

Abstract This study aimed to explore citizens’ emotional responses and issues of interest in the context of the coronavirus disease 2019 (COVID-19) pandemic. The dataset comprised 65,313 tweets with the location marked as New York State. The data collection period was four days of tweets when New York City imposed a lockdown order due to an increase in confirmed cases. Data analysis was performed using R Studio. The emotional responses in tweets were analyzed using the Bing and NRC (National Research Council Canada) dictionaries. The tweets’ central issue was identified by Text Network Analysis. When tweets were classified as either positive… More > Graphic Abstract

Umair Yousaf¹, Muhammad Asif¹, Shahbaz Ahmed¹, Noman Tahir¹, Azeem Irshad², Akber Abid Gardezi³, Muhammad Shafiq^4,*, Jin-Ghoo Choi⁴, Habib Hamam^5,6,7,8

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4165-4181, 2023, DOI:10.32604/cmc.2023.026607

Abstract The research volume increases at the study rate, causing massive text corpora. Due to these enormous text corpora, we are drowning in data and starving for information. Therefore, recent research employed different text mining approaches to extract information from this text corpus. These proposed approaches extract meaningful and precise phrases that effectively describe the text's information. These extracted phrases are commonly termed keyphrases. Further, these key phrases are employed to determine the different fields of study trends. Moreover, these key phrases can also be used to determine the spatiotemporal trends in the various research fields. In this research, the progress… More >

Fatema Nafa^1,*, Amal Babour², Austin Melton³

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.3, pp. 639-652, 2022, DOI:10.32604/cmes.2022.020084

Abstract The importance of prerequisites for education has recently become a promising research direction. This work proposes a statistical model for measuring dependencies in learning resources between knowledge units. Instructors are expected to present knowledge units in a semantically well-organized manner to facilitate students’ understanding of the material. The proposed model reveals how inner concepts of a knowledge unit are dependent on each other and on concepts not in the knowledge unit. To help understand the complexity of the inner concepts themselves, WordNet is included as an external knowledge base in this model. The goal is to develop a model that… More >

Sara A. Althubiti¹, Fayadh Alenezi², Romany F. Mansour^3,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3529-3544, 2022, DOI:10.32604/cmc.2022.028981

Abstract The recent advancements made in World Wide Web and social networking have eased the spread of fake news among people at a faster rate. At most of the times, the intention of fake news is to misinform the people and make manipulated societal insights. The spread of low-quality news in social networking sites has a negative influence upon people as well as the society. In order to overcome the ever-increasing dissemination of fake news, automated detection models are developed using Artificial Intelligence (AI) and Machine Learning (ML) methods. The latest advancements in Deep Learning (DL) models and complex Natural Language… More >

Hafsa Naveed¹, Abid Sohail², Jasni Mohamad Zain^3,*, Noman Saleem⁴, Rao Faizan Ali⁵, Shahid Anwar⁶

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 15-30, 2023, DOI:10.32604/iasc.2023.023277

Abstract Question and answer websites such as Quora, Stack Overflow, Yahoo Answers and Answer Bag are used by professionals. Multiple users post questions on these websites to get the answers from domain specific professionals. These websites are multilingual meaning they are available in many different languages. Current problem for these types of websites is to handle meaningless and irrelevant content. In this paper we have worked on the Quora insincere questions (questions which are based on false assumptions or questions which are trying to make a statement rather than seeking for helpful answers) dataset in order to identify user insincere questions,… More >

Zubair Nabi¹, Ramzan Talib^1,*, Muhammad Kashif Hanif¹, Muhammad Awais²

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1357-1374, 2022, DOI:10.32604/csse.2022.025712

Abstract Digitalization has changed the way of information processing, and new techniques of legal data processing are evolving. Text mining helps to analyze and search different court cases available in the form of digital text documents to extract case reasoning and related data. This sort of case processing helps professionals and researchers to refer the previous case with more accuracy in reduced time. The rapid development of judicial ontologies seems to deliver interesting problem solving to legal knowledge formalization. Mining context information through ontologies from corpora is a challenging and interesting field. This research paper presents a three tier contextual text… More >

Tsung-Yin Ou¹, Guan-Yu Lin², Hsin-Pin Fu¹, Shih-Chia Wei¹, Wen-Lung Tsai^3,*

Computer Systems Science and Engineering, Vol.42, No.3, pp. 881-897, 2022, DOI:10.32604/csse.2022.022637

Abstract Most real estate agents develop new objects by visiting unfamiliar clients, distributing leaflets, or browsing other real estate trading website platforms, whereas consumers often rely on websites to search and compare prices when purchasing real property. In addition to being time consuming, this search process renders it difficult for agents and consumers to understand the status changes of objects. In this study, Python is used to write web crawler and image recognition programs to capture object information from the web pages of real estate agents; perform data screening, arranging, and cleaning; compare the text of real estate object information; as… More >

Shahid Mehmood¹, Imran Ahmad¹, Muhammad Adnan Khan^1,2, Faheem Khan³, T. Whangbo^3,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5603-5618, 2022, DOI:10.32604/cmc.2022.023785

Abstract Education sector has witnessed several changes in the recent past. These changes have forced private universities into fierce competition with each other to get more students enrolled. This competition has resulted in the adoption of marketing practices by private universities similar to commercial brands. To get competitive gain, universities must observe and examine the students’ feedback on their own social media sites along with the social media sites of their competitors. This study presents a novel framework which integrates numerous analytical approaches including statistical analysis, sentiment analysis, and text mining to accomplish a competitive analysis of social media sites of… More >