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  • Open Access

    ARTICLE

    A Novel Collective User Web Behavior Simulation Method

    Hongri Liu1,2,3, Xu Zhang1,3, Jingjing Li1,3, Bailing Wang1,3,*

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2539-2553, 2021, DOI:10.32604/cmc.2021.012213

    Abstract

    A collective user web behavior simulation is an import means for generating a large-scale user network behavior in a network testbed or cyber range. Existing studies almost focus on individual web behavior analysis and prediction, which cannot simulate human dynamics that widely exist in large-scale users’ behaviors. To address these issues, we propose a novel collective user web behavior simulation method, in which an algorithm for constructing a connected virtual social network is proposed, and then a collective user web behavior simulation algorithm is designed on the virtual social network. In the simulation method, a new epidemic information dissemination algorithm… More >

  • Open Access

    ARTICLE

    An Emotion Analysis Method Using Multi-Channel Convolution Neural Network in Social Networks

    Xinxin Lu1,*, Hong Zhang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 281-297, 2020, DOI:10.32604/cmes.2020.010948

    Abstract As an interdisciplinary comprehensive subject involving multidisciplinary knowledge, emotional analysis has become a hot topic in psychology, health medicine and computer science. It has a high comprehensive and practical application value. Emotion research based on the social network is a relatively new topic in the field of psychology and medical health research. The text emotion analysis of college students also has an important research significance for the emotional state of students at a certain time or a certain period, so as to understand their normal state, abnormal state and the reason of state change from the information they wrote. In… More >

  • Open Access

    ARTICLE

    Research on Prediction Methods of Prevalence Perception under Information Exposure

    Weijin Jiang1, 2, 3, 4, Fang Ye1, 2, *, Wei Liu2, 3, Xiaoliang Liu1, 2, Guo Liang5, Yuhui Xu2, 3, Lina Tan1, 2

    CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2263-2275, 2020, DOI:10.32604/cmc.2020.010082

    Abstract With the rapid development of information technology, the explosive growth of data information has become a common challenge and opportunity. Social network services represented by WeChat, Weibo and Twitter, drive a large amount of information due to the continuous spread, evolution and emergence of users through these platforms. The dynamic modeling, analysis, and network information prediction, has very important research and application value, and plays a very important role in the discovery of popular events, personalized information recommendation, and early warning of bad information. For these reasons, this paper proposes an adaptive prediction algorithm for network information transmission. A popularity… More >

  • Open Access

    ARTICLE

    Topic Evolution Analysis in Social Networking Services: Taking Sina Weibo as an Example

    Yuhui Wang

    Computer Systems Science and Engineering, Vol.33, No.4, pp. 287-291, 2018, DOI:10.32604/csse.2018.33.287

    Abstract Event-related topics in social networking services are always the epitome of heated society issues, therefore determining the significance of analyzing its evolution patterns. In this paper, we present a comprehensive survey on the tweets about "ransomware" in Sina Weibo, a famous social networking service similar to twitter in China. The keyword corresponds to a global ransomware attack in May 2017, on which our example event-related topics are based. We collect text data from sina Weibo and vectorize each tweets, before using a dynamic topic model to discover the event-related topics. The results of the topic model are explainable enough and… More >

  • Open Access

    ARTICLE

    An Iteration-Based Differentially Private Social Network Data Release

    Tianqing Zhu1, Mengmeng Yang1, Ping Xiong2, Yang Xiang1, Wanlei Zhou1

    Computer Systems Science and Engineering, Vol.33, No.2, pp. 61-69, 2018, DOI:10.32604/csse.2018.33.061

    Abstract Online social networks provide an unprecedented opportunity for researchers to analysis various social phenomena. These network data is normally represented as graphs, which contain many sensitive individual information. Publish these graph data will violate users’ privacy. Differential privacy is one of the most influential privacy models that provides a rigorous privacy guarantee for data release. However, existing works on graph data publishing cannot provide accurate results when releasing a large number of queries. In this paper, we propose a graph update method transferring the query release problem to an iteration process, in which a large set of queries are used… More >

  • Open Access

    ARTICLE

    Accurate Location Prediction of Social‐Users Using mHMM

    Ahsan Hussain, Bettahally N. Keshavamurthy, Ravi Prasad K. Jagannath

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 473-486, 2019, DOI:10.31209/2018.11007092

    Abstract Prediction space of distinct check-in locations in Location-Based Social Networks is a challenge. In this paper, a thorough analysis of Foursquare Check-ins is done. Based on previous check-in sequences, next location of social-users is accurately predicted using multinomial-Hidden Markov Model (mHMM) with Steady-State probabilities. This information benefits security-agencies in tracking suspects and restaurant-owners to predict their customers’ arrivals at different venues on given days. Higher accuracy and Steady-State venuepopularities obtained for location-prediction using the proposed method, outperform various other baseline methods. More >

  • Open Access

    ARTICLE

    Semi-GSGCN: Social Robot Detection Research with Graph Neural Network

    Xiujuan Wang1, Qianqian Zheng1, *, Kangfeng Zheng2, Yi Sui1, Jiayue Zhang1

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 617-638, 2020, DOI:10.32604/cmc.2020.011165

    Abstract Malicious social robots are the disseminators of malicious information on social networks, which seriously affect information security and network environments. Efficient and reliable classification of social robots is crucial for detecting information manipulation in social networks. Supervised classification based on manual feature extraction has been widely used in social robot detection. However, these methods not only involve the privacy of users but also ignore hidden feature information, especially the graph feature, and the label utilization rate of semi-supervised algorithms is low. Aiming at the problems of shallow feature extraction and low label utilization rate in existing social network robot detection… More >

  • Open Access

    ARTICLE

    Influence Diffusion Model in Multiplex Networks

    Senbo Chen1, 3, *, Wenan Tan1, 2

    CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 345-358, 2020, DOI:10.32604/cmc.2020.09807

    Abstract The problem of influence maximizing in social networks refers to obtaining a set of nodes of a specified size under a specific propagation model so that the aggregation of the node-set in the network has the greatest influence. Up to now, most of the research has tended to focus on monolayer network rather than on multiplex networks. But in the real world, most individuals usually exist in multiplex networks. Multiplex networks are substantially different as compared with those of a monolayer network. In this paper, we integrate the multi-relationship of agents in multiplex networks by considering the existing and relevant… More >

  • Open Access

    ARTICLE

    Access Control Policy Based on Friend Circle

    Qin Liu1, Tinghuai Ma1, 2, *, Fan Xing1, Yuan Tian3, Abdullah Al-Dhelaan3, Mohammed Al-Dhelaan3

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1143-1159, 2020, DOI:10.32604/cmc.2020.04949

    Abstract Nowadays, the scale of the user’s personal social network (personal network, a network of the user and their friends, where the user we call “center user”) is becoming larger and more complex. It is difficult to find a suitable way to manage them automatically. In order to solve this problem, we propose an access control model for social network to protect the privacy of the central users, which achieves the access control accurately and automatically. Based on the hybrid friend circle detection algorithm, we consider the aspects of direct judgment, indirect trust judgment and malicious users, a set of multi-angle… More >

  • Open Access

    ARTICLE

    User Profile System Based on Sentiment Analysis for Mobile Edge Computing

    Sang-Min Park1, Young-Gab Kim2, *

    CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 569-590, 2020, DOI:10.32604/cmc.2020.08666

    Abstract Emotions of users do not converge in a single application but are scattered across diverse applications. Mobile devices are the closest media for handling user data and these devices have the advantage of integrating private user information and emotions spread over different applications. In this paper, we first analyze user profile on a mobile device by describing the problem of the user sentiment profile system in terms of data granularity, media diversity, and server-side solution. Fine-grained data requires additional data and structural analysis in mobile devices. Media diversity requires standard parameters to integrate user data from various applications. A server-side… More >

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