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  • 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 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 More >

  • Open Access

    ARTICLE

    Research on Privacy Disclosure Detection Method in Social Networks Based on Multi-Dimensional Deep Learning

    Yabin Xu1, 2, *, Xuyang Meng1, Yangyang Li3, Xiaowei Xu4, *

    CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 137-155, 2020, DOI:10.32604/cmc.2020.05825

    Abstract In order to effectively detect the privacy that may be leaked through social networks and avoid unnecessary harm to users, this paper takes microblog as the research object to study the detection of privacy disclosure in social networks. First, we perform fast privacy leak detection on the currently published text based on the fastText model. In the case that the text to be published contains certain private information, we fully consider the aggregation effect of the private information leaked by different channels, and establish a convolution neural network model based on multi-dimensional features (MF-CNN) to 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

    SNES: Social-Network-Oriented Public Opinion Monitoring Platform Based on ElasticSearch

    Chuiju You1, Dongjie Zhu2,*, Yundong Sun2, Anshan Ye3, Gangshan Wu4, Ning Cao1, Jinming Qiu1, Helen Min Zhou5

    CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1271-1283, 2019, DOI:10.32604/cmc.2019.06133

    Abstract With the rapid development of social network, public opinion monitoring based on social networks is becoming more and more important. Many platforms have achieved some success in public opinion monitoring. However, these platforms cannot perform well in scalability, fault tolerance, and real-time performance. In this paper, we propose a novel social-network-oriented public opinion monitoring platform based on ElasticSearch (SNES). Firstly, SNES integrates the module of distributed crawler cluster, which provides real-time social media data access. Secondly, SNES integrates ElasticSearch which can store and retrieve massive unstructured data in near real time. Finally, we design subscription More >

  • Open Access

    ARTICLE

    MMLUP: Multi-Source & Multi-Task Learning for User Profiles in Social Network

    Dongjie Zhu1, Yuhua Wang1, Chuiju You2,*, Jinming Qiu2,3, Ning Cao2, Chenjing Gong4, Guohua Yang5, Helen Min Zhou6

    CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1105-1115, 2019, DOI:10.32604/cmc.2019.06041

    Abstract With the rapid development of the mobile Internet, users generate massive data in different forms in social network every day, and different characteristics of users are reflected by these social media data. How to integrate multiple heterogeneous information and establish user profiles from multiple perspectives plays an important role in providing personalized services, marketing, and recommendation systems. In this paper, we propose Multi-source & Multi-task Learning for User Profiles in Social Network which integrates multiple social data sources and contains a multi-task learning framework to simultaneously predict various attributes of a user. Firstly, we design More >

  • Open Access

    ARTICLE

    Research on the Association of Mobile Social Network Users Privacy Information Based on Big Data Analysis

    Pingshui Wang1,*, Zecheng Wang1, Qinjuan Ma1

    Journal of Information Hiding and Privacy Protection, Vol.1, No.1, pp. 35-42, 2019, DOI:10.32604/jihpp.2019.05942

    Abstract The issue of privacy protection for mobile social networks is a frontier topic in the field of social network applications. The existing researches on user privacy protection in mobile social network mainly focus on privacy preserving data publishing and access control. There is little research on the association of user privacy information, so it is not easy to design personalized privacy protection strategy, but also increase the complexity of user privacy settings. Therefore, this paper concentrates on the association of user privacy information taking big data analysis tools, so as to provide data support for More >

  • Open Access

    ARTICLE

    An Influence Maximization Algorithm Based on the Influence Propagation Range of Nodes

    Yong Hua1,Bolun Chen1,2,∗,Yan Yuan1, Guochang Zhu1, Fenfen Li1

    Journal on Internet of Things, Vol.1, No.2, pp. 77-88, 2019, DOI:10.32604/jiot.2019.05941

    Abstract The problem of influence maximization in the social network G is to find k seed nodes with the maximum influence. The seed set S has a wider range of influence in the social network G than other same-size node sets. The influence of a node is usually established by using the IC model (Independent Cascade model) with a considerable amount of Monte Carlo simulations used to approximate the influence of the node. In addition, an approximate effect (1-1/e) is obtained, when the number of Monte Carlo simulations is 10000 and the probability of propagation is More >

  • Open Access

    ARTICLE

    Personalized Privacy Protecting Model in Mobile Social Network

    Pingshui Wang1,*, Zecheng Wang1, Tao Chen1,2, Qinjuan Ma1

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 533-546, 2019, DOI:10.32604/cmc.2019.05570

    Abstract With the rapid development of the new generation of information technology, the analysis of mobile social network big data is getting deeper and deeper. At the same time, the risk of privacy disclosure in social network is also very obvious. In this paper, we summarize the main access control model in mobile social network, analyze their contribution and point out their disadvantages. On this basis, a practical privacy policy is defined through authorization model supporting personalized privacy preferences. Experiments have been conducted on synthetic data sets. The result shows that the proposed privacy protecting model More >

  • Open Access

    ARTICLE

    An Influence Maximization Algorithm Based on the Mixed Importance of Nodes

    Yong Hua1, Bolun Chen1,2,*, Yan Yuan1, Guochang Zhu1, Jialin Ma1

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 517-531, 2019, DOI:10.32604/cmc.2019.05278

    Abstract The influence maximization is the problem of finding k seed nodes that maximize the scope of influence in a social network. Therefore, the comprehensive influence of node needs to be considered, when we choose the most influential node set consisted of k seed nodes. On account of the traditional methods used to measure the influence of nodes, such as degree centrality, betweenness centrality and closeness centrality, consider only a single aspect of the influence of node, so the influence measured by traditional methods mentioned above of node is not accurate. In this paper, we obtain the More >

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