Nahla H. Barakat^*, Ahmed H. ElSabbagh

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1207-1224, 2022, DOI:10.32604/iasc.2022.022104

Abstract Social media recently became convenient platforms for different groups with common concerns to share their experiences, including Adverse Drug Reactions (ADRs). In this paper, we propose a two stage intelligent algorithm which we call “Simi_to_Prob”, that utilizes social media forums; for ranking ADRs, and evaluating the ADRs prevalence considering different age and gender groups as its first stage. In the second stage, ADRs are predicted utilizing a different data set from the Food and Drug Administration (FDA). In particular, Natural Language Processing (NLP) is used on social media to extract ranked lists of ADRs, which are then validated using novel… More >

Fiaz Majeed¹, Noman Yousaf², Muhammad Shafiq^3,*, Mohammed Ahmed Basheikh⁴, Wazir Zada Khan⁵, Akber Abid Gardezi⁶, Waqar Aslam⁷, Jin-Ghoo Choi³

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 15-30, 2022, DOI:10.32604/iasc.2022.015685

Abstract Social networks have become an important venue to express the feelings of their users on a large scale. People are intuitive to use social networks to express their feelings, discuss ideas, and invite folks to take suggestions. Every social media user has a circle of friends. The suggestions of these friends are considered important contributions. Users pay more attention to suggestions provided by their friends or close friends. However, as the content on the Internet increases day by day, user satisfaction decreases at the same rate due to unsatisfactory search results. In this regard, different recommender systems have been developed… More >

Dharmendra Dangi^*, Amit Bhagat, Dheeraj Kumar Dixit

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5399-5419, 2022, DOI:10.32604/cmc.2022.020431

Abstract There are various intense forces causing customers to use evaluated data when using social media platforms and microblogging sites. Today, customers throughout the world share their points of view on all kinds of topics through these sources. The massive volume of data created by these customers makes it impossible to analyze such data manually. Therefore, an efficient and intelligent method for evaluating social media data and their divergence needs to be developed. Today, various types of equipment and techniques are available for automatically estimating the classification of sentiments. Sentiment analysis involves determining people's emotions using facial expressions. Sentiment analysis can… More >

Norjihan Binti Abdul Ghani^1,*, Suraya Hamid¹, Muneer Ahmad¹, Younes Saadi¹, N.Z. Jhanjhi², Mohammed A. Alzain³, Mehedi Masud⁴

Computer Systems Science and Engineering, Vol.40, No.3, pp. 913-926, 2022, DOI:10.32604/csse.2022.018467

Abstract The world health organization (WHO) terms dengue as a serious illness that impacts almost half of the world’s population and carries no specific treatment. Early and accurate detection of spread in affected regions can save precious lives. Despite the severity of the disease, a few noticeable works can be found that involve sentiment analysis to mine accurate intuitions from the social media text streams. However, the massive data explosion in recent years has led to difficulties in terms of storing and processing large amounts of data, as reliable mechanisms to gather the data and suitable techniques to extract meaningful insights… More >

Shynar Mussiraliyeva¹, Batyrkhan Omarov^1,*, Paul Yoo^1,2, Milana Bolatbek¹

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 915-934, 2022, DOI:10.32604/cmc.2022.019189

Abstract In this research paper, we propose a corpus for the task of detecting religious extremism in social networks and open sources and compare various machine learning algorithms for the binary classification problem using a previously created corpus, thereby checking whether it is possible to detect extremist messages in the Kazakh language. To do this, the authors trained models using six classic machine-learning algorithms such as Support Vector Machine, Decision Tree, Random Forest, K Nearest Neighbors, Naive Bayes, and Logistic Regression. To increase the accuracy of detecting extremist texts, we used various characteristics such as Statistical Features, TF-IDF, POS, LIWC, and… More >

Sultan Noman Qasem^1,2, Mohammed Al-Sarem^3,4, Faisal Saeed^3,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1721-1747, 2022, DOI:10.32604/cmc.2022.018972

Abstract Rumors regarding epidemic diseases such as COVID 19, medicines and treatments, diagnostic methods and public emergencies can have harmful impacts on health and political, social and other aspects of people’s lives, especially during emergency situations and health crises. With huge amounts of content being posted to social media every second during these situations, it becomes very difficult to detect fake news (rumors) that poses threats to the stability and sustainability of the healthcare sector. A rumor is defined as a statement for which truthfulness has not been verified. During COVID 19, people found difficulty in obtaining the most truthful news… More >

Jari Jussila¹, Eman Alkhammash^2,*, Norah Saleh Alghamdi³, Prashanth Madhala⁴, Mohammad Ayoub Khan⁵

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1845-1856, 2022, DOI:10.32604/cmc.2022.017284

Abstract Social media platforms provide new value for markets and research companies. This article explores the use of social media data to enhance customer value propositions. The case study involves a company that develops wearable Internet of Things (IoT) devices and services for stress management. Netnography and semantic annotation for recognizing and categorizing the context of tweets are conducted to gain a better understanding of users’ stress management practices. The aim is to analyze the tweets about stress management practices and to identify the context from the tweets. Thereafter, we map the tweets on pleasure and arousal to elicit customer insights.… More >

Yonghun Jang, Chang-Hyeon Park, Dong-Gun Lee, Yeong-Seok Seo^*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3563-3579, 2021, DOI:10.32604/cmc.2021.018901

Abstract Following the development of communication techniques and smart devices, the era of Artificial Intelligence (AI) and big data has arrived. The increased connectivity, referred to as hyper-connectivity, has led to the development of smart cities. People in these smart cities can access numerous online contents and are always connected. These developments, however, also lead to a lack of standardization and consistency in the propagation of information throughout communities due to the consumption of information through social media channels. Information cannot often be verified, which can confuse the users. The increasing influence of social media has thus led to the emergence… More >

Shady Y. El-mashad¹, Amani M. Yassen¹, Abdulwahab K. Alsammak¹, Basem M. Elhalawany^2,*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3857-3870, 2021, DOI:10.32604/cmc.2021.018660

Abstract The last decade shows an explosion of using social media, which raises several challenges related to the security of personal files including images. These challenges include modifying, illegal copying, identity fraud, copyright protection and ownership of images. Traditional digital watermarking techniques embed digital information inside another digital information without affecting the visual quality for security purposes. In this paper, we propose a hybrid digital watermarking and image processing approach to improve the image security level. Specifically, variants of the widely used Least-Significant Bit (LSB) watermarking technique are merged with a blob detection algorithm to embed information into the boundary pixels… More >

Mahmoud Oglah Al Hasan Baniata^*, Sohail Asghar

Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 821-836, 2021, DOI:10.32604/iasc.2021.018612

Abstract The advancement in electronic devices and communication technologies in social media have introduced major changes in today’s communication and people have accepted such communicational habits at a rapid pace. The changes involve the way people started interacting with each other, and modern mean of discovering new groups of people, and individuals with similar mindsets, mutual interests, and ideas to share with. As far as the communities are concerned, there are so many social drives (such as “Say No to Plastic”) that need to be discussed on a certain platform for their promotion. Although, it’s quit is challenging, but with the… More >