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  • Open Access

    ARTICLE

    Improved Key Node Recognition Method of Social Network Based on PageRank Algorithm

    Lei Hong1, Yiji Qian1,*, Chaofan Gong2, Yurui Zhang1, Xin Zhou3

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1887-1903, 2023, DOI:10.32604/cmc.2023.029180 - 22 September 2022

    Abstract The types and functions of social networking sites are becoming more abundant with the prevalence of self-media culture, and the number of daily active users of social networking sites represented by Weibo and Zhihu continues to expand. There are key node users in social networks. Compared with ordinary users, their influence is greater, their radiation range is wider, and their information transmission capabilities are better. The key node users playimportant roles in public opinion monitoring and hot event prediction when evaluating the criticality of nodes in social networking sites. In order to solve the problems… More >

  • Open Access

    ARTICLE

    Multi-attribute Group Decision-making Based on Hesitant Bipolar-valued Fuzzy Information and Social Network

    Dhanalakshmi R1, Sovan Samanta2, Arun Kumar Sivaraman3, Jeong Gon Lee4,*, Balasundaram A5, Sanamdikar Sanjay Tanaji6, Priya Ravindran7

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 1939-1950, 2023, DOI:10.32604/csse.2023.026254 - 01 August 2022

    Abstract Fuzzy sets have undergone several expansions and generalisations in the literature, including Atanasov’s intuitionistic fuzzy sets, type 2 fuzzy sets, and fuzzy multisets, to name a few. They can be regarded as fuzzy multisets from a formal standpoint; nevertheless, their interpretation differs from the two other approaches to fuzzy multisets that are currently available. Hesitating fuzzy sets (HFS) are very useful if consultants have hesitation in dealing with group decision-making problems between several possible memberships. However, these possible memberships can be not only crisp values in [0,1], but also interval values during a practical evaluation… More >

  • Open Access

    ARTICLE

    A Parallel Approach for Sentiment Analysis on Social Networks Using Spark

    M. Mohamed Iqbal1,*, K. Latha2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1831-1842, 2023, DOI:10.32604/iasc.2023.029036 - 19 July 2022

    Abstract The public is increasingly using social media platforms such as Twitter and Facebook to express their views on a variety of topics. As a result, social media has emerged as the most effective and largest open source for obtaining public opinion. Single node computational methods are inefficient for sentiment analysis on such large datasets. Supercomputers or parallel or distributed processing are two options for dealing with such large amounts of data. Most parallel programming frameworks, such as MPI (Message Processing Interface), are difficult to use and scale in environments where supercomputers are expensive. Using the… More >

  • Open Access

    ARTICLE

    Detection of Toxic Content on Social Networking Platforms Using Fine Tuned ULMFiT Model

    Hafsa Naveed1, Abid Sohail2, Jasni Mohamad Zain3,*, 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 - 06 June 2022

    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 More >

  • Open Access

    ARTICLE

    Social Opinion Network Analytics in Community Based Customer Churn Prediction

    Ayodeji O. J Ibitoye1,*, Olufade F. W Onifade2

    Journal on Big Data, Vol.4, No.2, pp. 87-95, 2022, DOI:10.32604/jbd.2022.024533 - 31 October 2022

    Abstract Community based churn prediction, or the assignment of recognising the influence of a customer’s community in churn prediction has become an important concern for firms in many different industries. While churn prediction until recent times have focused only on transactional dataset (targeted approach), the untargeted approach through product advisement, digital marketing and expressions in customer’s opinion on the social media like Twitter, have not been fully harnessed. Although this data source has become an important influencing factor with lasting impact on churn management. Since Social Network Analysis (SNA) has become a blended approach for churn… More >

  • Open Access

    ARTICLE

    Model for Generating Scale-Free Artificial Social Networks Using Small-World Networks

    Farhan Amin, Gyu Sang Choi*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6367-6391, 2022, DOI:10.32604/cmc.2022.029927 - 28 July 2022

    Abstract The Internet of Things (IoT) has the potential to be applied to social networks due to innovative characteristics and sophisticated solutions that challenge traditional uses. Social network analysis (SNA) is a good example that has recently gained a lot of scientific attention. It has its roots in social and economic research, as well as the evaluation of network science, such as graph theory. Scientists in this area have subverted predefined theories, offering revolutionary ones regarding interconnected networks, and they have highlighted the mystery of six degrees of separation with confirmation of the small-world phenomenon. The… More >

  • Open Access

    ARTICLE

    SPN-Based Performance Analysis of Multiple Users’ Behaviors for SNS

    Zhiguo Hong1,*, Yongbin Wang2,3, Minyong Shi4

    Journal of Information Hiding and Privacy Protection, Vol.4, No.1, pp. 1-13, 2022, DOI:10.32604/jihpp.2022.026440 - 17 June 2022

    Abstract With the rapid development of various applications of Information Technology, big data are increasingly generated by social network services (SNS) nowadays. The designers and providers of SNS distribute different client applications for PC, Mobile phone, IPTV etc., so that users can obtain related service via mobile or traditional Internet. Good scalability and considerably short time delay are important indices for evaluating social network systems. As a result, investigating and mining the principle of users’ behaviors is an important issue which can guide service providers to establish optimal systems with SNS. On the basis of analyzing… More >

  • Open Access

    ARTICLE

    SAFT-VNDN: A Socially-Aware Forwarding Technique in Vehicular Named Data Networking

    Amel Boudelaa1, Zohra Abdelhafidi1, Nasreddine Lagraa1, Chaker Abdelaziz Kerrache1, Muhammad Bilal2, Daehan Kwak3,*, Mohamed Bachir Yagoubi1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2495-2512, 2022, DOI:10.32604/cmc.2022.028619 - 16 June 2022

    Abstract Vehicular Social Networks (VSNs) is the bridge of social networks and Vehicular Ad-Hoc Networks (VANETs). VSNs are promising as they allow the exchange of various types of contents in large-scale through Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication protocols. Vehicular Named Data Networking (VNDN) is an auspicious communication paradigm for the challenging VSN environment since it can optimize content dissemination by decoupling contents from their physical locations. However, content dissemination and caching represent crucial challenges in VSNs due to short link lifetime and intermittent connectivity caused by vehicles’ high mobility. Our aim with this paper is… More >

  • Open Access

    ARTICLE

    Glowworm Optimization with Deep Learning Enabled Cybersecurity in Social Networks

    Ashit Kumar Dutta1,*, Basit Qureshi2, Yasser Albagory3, Majed Alsanea4, Anas Waleed AbulFaraj5, Abdul Rahaman Wahab Sait6

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 2097-2110, 2022, DOI:10.32604/iasc.2022.027500 - 25 May 2022

    Abstract Recently, the exponential utilization of Internet has posed several cybersecurity issues in social networks. Particularly, cyberbulling becomes a common threat to users in real time environment. Automated detection and classification of cyberbullying in social networks become an essential task, which can be derived by the use of machine learning (ML) and deep learning (DL) approaches. Since the hyperparameters of the DL model are important for optimal outcomes, appropriate tuning strategy becomes important by the use of metaheuristic optimization algorithms. In this study, an effective glowworm swarm optimization (GSO) with deep neural network (DNN) model named… More >

  • Open Access

    ARTICLE

    Customized Share Level Monitoring System for Users in OSN-Third Party Applications

    T. Shanmuigapriya1,*, S. Swamynathan2, Thiruvaazhi Uloli3

    Computer Systems Science and Engineering, Vol.43, No.3, pp. 1327-1339, 2022, DOI:10.32604/csse.2022.024440 - 09 May 2022

    Abstract Preserving privacy of the user is a very critical requirement to be met with all the international laws like GDPR, California privacy protection act and many other bills in place. On the other hand, Online Social Networks (OSN) has a wide spread recognition among the users, as a means of virtual communication. OSN may also acts as an identity provider for both internal and external applications. While it provides a simplified identification and authentication function to users across multiple applications, it also opens the users to a new spectrum of privacy threats. The privacy breaches… More >

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