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  • Open Access

    ARTICLE

    Applying Machine Learning Techniques for Religious Extremism Detection on Online User Contents

    Shynar Mussiraliyeva1, Batyrkhan Omarov1,*, Paul Yoo1,2, Milana Bolatbek1

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 915-934, 2022, DOI:10.32604/cmc.2022.019189 - 07 September 2021

    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 More >

  • Open Access

    ARTICLE

    An Ensemble Learning Based Approach for Detecting and Tracking COVID19 Rumors

    Sultan Noman Qasem1,2, Mohammed Al-Sarem3,4, Faisal Saeed3,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1721-1747, 2022, DOI:10.32604/cmc.2022.018972 - 07 September 2021

    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… More >

  • Open Access

    ARTICLE

    A Netnographic-Based Semantic Analysis of Tweet Contents for Stress Management

    Jari Jussila1, Eman Alkhammash2,*, 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 - 07 September 2021

    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… More >

  • Open Access

    ARTICLE

    Linux Kali for Social Media User Location: A Target-Oriented Social Media Software Vulnerability Detection

    Adnan Alam Khan1,2,*, Qamar-ul-Arfeen1

    Journal of Cyber Security, Vol.3, No.4, pp. 201-205, 2021, DOI:10.32604/jcs.2021.024614 - 09 February 2022

    Abstract Technology is expanding like a mushroom, there are various benefits of technology, in contrary users are facing serious losses by this technology. Furthermore, people lost their lives, their loved ones, brain-related diseases, etc. The industry is eager to get one technology that can secure their finance-related matters, personal videos or pictures, precious contact numbers, and their current location. Things are going worst because every software has some sort of legacy, deficiency, and shortcomings through which exploiters gain access to any software. There are various ways to get illegitimate access but on the top is Linux More >

  • Open Access

    ARTICLE

    Fake News Detection on Social Media: A Temporal-Based Approach

    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 - 24 August 2021

    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… More >

  • Open Access

    ARTICLE

    Local Features-Based Watermarking for Image Security in Social Media

    Shady Y. El-mashad1, Amani M. Yassen1, Abdulwahab K. Alsammak1, Basem M. Elhalawany2,*

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3857-3870, 2021, DOI:10.32604/cmc.2021.018660 - 24 August 2021

    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 More >

  • Open Access

    ARTICLE

    Sentiment Analytics: Extraction of Challenging Influencing Factors from COVID-19 Pandemics

    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 - 20 August 2021

    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… More >

  • Open Access

    ARTICLE

    Multi-Class Sentiment Analysis of Social Media Data with Machine Learning Algorithms

    Galimkair Mutanov, Vladislav Karyukin*, Zhanl Mamykova

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 913-930, 2021, DOI:10.32604/cmc.2021.017827 - 04 June 2021

    Abstract The volume of social media data on the Internet is constantly growing. This has created a substantial research field for data analysts. The diversity of articles, posts, and comments on news websites and social networks astonishes imagination. Nevertheless, most researchers focus on posts on Twitter that have a specific format and length restriction. The majority of them are written in the English language. As relatively few works have paid attention to sentiment analysis in the Russian and Kazakh languages, this article thoroughly analyzes news posts in the Kazakhstan media space. The amassed datasets include texts… More >

  • Open Access

    ARTICLE

    Detecting Man-in-the-Middle Attack in Fog Computing for Social Media

    Farouq Aliyu1,*, Tarek Sheltami1, Ashraf Mahmoud1, Louai Al-Awami1, Ansar Yasar2

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1159-1181, 2021, DOI:10.32604/cmc.2021.016938 - 04 June 2021

    Abstract Fog computing (FC) is a networking paradigm where wireless devices known as fog nodes are placed at the edge of the network (close to the Internet of Things (IoT) devices). Fog nodes provide services in lieu of the cloud. Thus, improving the performance of the network and making it attractive to social media-based systems. Security issues are one of the most challenges encountered in FC. In this paper, we propose an anomaly-based Intrusion Detection and Prevention System (IDPS) against Man-in-the-Middle (MITM) attack in the fog layer. The system uses special nodes known as Intrusion Detection… More >

  • Open Access

    ARTICLE

    Development of Social Media Analytics System for Emergency Event Detection and Crisis Management

    Shaheen Khatoon1,*, Majed A. Alshamari1, Amna Asif1, Md Maruf Hasan1, Sherif Abdou2, Khaled Mostafa Elsayed3, Mohsen Rashwan4

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3079-3100, 2021, DOI:10.32604/cmc.2021.017371 - 06 May 2021

    Abstract Social media platforms have proven to be effective for information gathering during emergency events caused by natural or human-made disasters. Emergency response authorities, law enforcement agencies, and the public can use this information to gain situational awareness and improve disaster response. In case of emergencies, rapid responses are needed to address victims’ requests for help. The research community has developed many social media platforms and used them effectively for emergency response and coordination in the past. However, most of the present deployments of platforms in crisis management are not automated, and their operational success largely… More >

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