Daniyal Amankeldin¹, Lyailya Kurmangaziyeva², Ayman Mailybayeva², Natalya Glazyrina¹, Ainur Zhumadillayeva^1,*, Nurzhamal Karasheva³

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1091-1108, 2023, DOI:10.32604/csse.2023.039503

Abstract This paper proposes a deep neural network (DNN) approach for detecting fake profiles in social networks. The DNN model is trained on a large dataset of real and fake profiles and is designed to learn complex features and patterns that distinguish between the two types of profiles. In addition, the present research aims to determine the minimum set of profile data required for recognizing fake profiles on Facebook and propose the deep convolutional neural network method for fake accounts detection on social networks, which has been developed using 16 features based on content-based and profile-based features. The results demonstrated that… More >

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 >

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

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 Improved Ant Lion Optimizer with… More >

Wenlong Zhu^1,*, Yu Miao¹, Shuangshuang Yang², Zuozheng Lian¹, Lianhe Cui¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3111-3131, 2023, DOI:10.32604/cmc.2023.036159

Abstract Influence maximization of temporal social networks (IMT) is a problem that aims to find the most influential set of nodes in the temporal network so that their information can be the most widely spread. To solve the IMT problem, we propose an influence maximization algorithm based on an improved K-shell method, namely improved K-shell in temporal social networks (KT). The algorithm takes into account the global and local structures of temporal social networks. First, to obtain the kernel value Ks of each node, in the global scope, it layers the network according to the temporal characteristic of nodes by improving… More >

R. Gnanakumari^1,*, P. Vijayalakshmi²

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2719-2730, 2023, DOI:10.32604/iasc.2023.034145

Abstract In social data analytics, Virtual Community (VC) detection is a primary challenge in discovering user relationships and enhancing social recommendations. VC formation is used for personal interaction between communities. But the usual methods didn’t find the Suspicious Behaviour (SB) needed to make a VC. The Generalized Jaccard Suspicious Behavior Similarity-based Recurrent Deep Neural Network Classification and Ranking (GJSBS-RDNNCR) Model addresses these issues. The GJSBS-RDNNCR model comprises four layers for VC formation in Social Networks (SN). In the GJSBS-RDNNCR model, the SN is given as an input at the input layer. After that, the User’s Behaviors (UB) are extracted in the… More >

Muhammad Riaz¹, Masooma Raza Hashmi¹, Faruk Karaaslan², Aslıhan Sezgin³, Mohammed M. Ali Al Shamiri^4,5,*, Mohammed M. Khalaf^6,7

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1759-1783, 2023, DOI:10.32604/cmes.2023.023327

Abstract This paper aims to introduce the novel concept of neutrosophic crisp soft set (NCSS), including various types of neutrosophic crisp soft sets (NCSSs) and their fundamental operations. We define NCS-mapping and its inverse NCS-mapping between two NCS-classes. We develop a robust mathematical modeling with the help of NCS-mapping to analyze the emerging trends in social networking systems (SNSs) for our various generations. We investigate the advantages, disadvantages, and natural aspects of SNSs for five generations. With the changing of the generations, it is analyzed that emerging trends and the benefits of SNSs are increasing day by day. The suggested modeling… More > Graphic Abstract

Diana T. Mosa^1,2, Mahmoud Y. Shams^3,*, Amr A. Abohany², El-Sayed M. El-kenawy⁴, M. Thabet⁵

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1271-1290, 2023, DOI:10.32604/cmc.2023.036422

Abstract Cyber Attacks are critical and destructive to all industry sectors. They affect social engineering by allowing unapproved access to a Personal Computer (PC) that breaks the corrupted system and threatens humans. The defense of security requires understanding the nature of Cyber Attacks, so prevention becomes easy and accurate by acquiring sufficient knowledge about various features of Cyber Attacks. Cyber-Security proposes appropriate actions that can handle and block attacks. A phishing attack is one of the cybercrimes in which users follow a link to illegal websites that will persuade them to divulge their private information. One of the online security challenges… More >

Rupali Gangarde^1,2,*, Amit Sharma³, Ambika Pawar⁴

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2171-2190, 2023, DOI:10.32604/cmc.2023.035559

Abstract Online Social Networks (OSN) sites allow end-users to share a great deal of information, which may also contain sensitive information, that may be subject to commercial or non-commercial privacy attacks. As a result, guaranteeing various levels of privacy is critical while publishing data by OSNs. The clustering-based solutions proved an effective mechanism to achieve the privacy notions in OSNs. But fixed clustering limits the performance and scalability. Data utility degrades with increased privacy, so balancing the privacy utility trade-off is an open research issue. The research has proposed a novel privacy preservation model using the enhanced clustering mechanism to overcome… More >

C. Suganthini^*, R. Baskaran

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1715-1731, 2023, DOI:10.32604/iasc.2023.034019

Abstract In online social networks (OSN), they generate several specific user activities daily, corresponding to the billions of data points shared. However, although users exhibit significant interest in social media, they are uninterested in the content, discussions, or opinions available on certain sites. Therefore, this study aims to identify influential communities and understand user behavior across networks in the information diffusion process. Social media platforms, such as Facebook and Twitter, extract data to analyze the information diffusion process, based on which they cascade information among the individuals in the network. Therefore, this study proposes an influential information diffusion model that identifies… More >

Farah Batool¹, Abdul Rehman², Dongsun Kim^2,*, Assad Abbas¹, Raheel Nawaz³, Tahir Mustafa Madni¹

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6535-6553, 2023, DOI:10.32604/cmc.2023.033832

Abstract The authors propose an informed search greedy approach that efficiently identifies the influencer nodes in the social Internet of Things with the ability to provide legitimate information. Primarily, the proposed approach minimizes the network size and eliminates undesirable connections. For that, the proposed approach ranks each of the nodes and prioritizes them to identify an authentic influencer. Therefore, the proposed approach discards the nodes having a rank (α) lesser than 0.5 to reduce the network complexity. α is the variable value represents the rank of each node that varies between 0 to 1. Node with the higher value of α… More >