Computational Social Networks最新文献_第10页

A study on the influential neighbors to maximize information diffusion in online social networks 在线社交网络中影响信息传播最大化的邻居研究

Computational Social Networks Pub Date : 2015-02-27 DOI: 10.1186/s40649-015-0013-8

Hyoungshick Kim, K. Beznosov, Eiko Yoneki

引用次数: 23

Power and loyalty defined by proximity to influential relations 权力和忠诚取决于是否接近有影响力的关系

Computational Social Networks Pub Date : 2015-02-24 DOI: 10.1186/s40649-014-0009-9

Dror Fidler

引用次数: 3

A strategic model for network formation 网络形成的战略模型

Computational Social Networks Pub Date : 2015-02-15 DOI: 10.1186/s40649-014-0008-x

Omid Atabati, Babak Farzad

引用次数: 1

Analysis and control of information diffusion dictated by user interest in generalized networks. 广义网络中用户兴趣决定的信息扩散分析与控制。

Computational Social Networks Pub Date : 2015-01-01 Epub Date: 2015-12-02 DOI: 10.1186/s40649-015-0025-4

Eleni Stai, Vasileios Karyotis, Symeon Papavassiliou

{"title":"Analysis and control of information diffusion dictated by user interest in generalized networks.","authors":"Eleni Stai, Vasileios Karyotis, Symeon Papavassiliou","doi":"10.1186/s40649-015-0025-4","DOIUrl":"https://doi.org/10.1186/s40649-015-0025-4","url":null,"abstract":"The diffusion of useful information in generalized networks, such as those consisting of wireless physical substrates and social network overlays is very important for theoretical and practical applications. Contrary to previous works, we focus on the impact of user interest and its features (e.g., interest periodicity) on the dynamics and control of diffusion of useful information within such complex wireless-social systems. By considering the impact of temporal and topical variations of users interests, e.g., seasonal periodicity of interest in summer vacation advertisements which spread more effectively during Spring-Summer months, we develop an epidemic-based mathematical framework for modeling and analyzing such information dissemination processes and use three indicative operational scenarios to demonstrate the solutions and results that can be obtained by the corresponding differential equation-based formalism. We then develop an optimal control framework subject to the above information diffusion modeling that allows controlling the trade-off between information propagation efficiency and the associated cost, by considering and leveraging on the impact that user interests have on the diffusion processes. By analysis and extensive simulations, significant outcomes are obtained on the impact of each network layer and the associated interest parameters on the dynamics of useful information diffusion. Furthermore, several behavioral properties of the optimal control of the useful information diffusion with respect to the number of infected/informed nodes and the evolving user interest are shown through analysis and verified via simulations. Specifically, a key finding is that low interest-related diffusion can be aided by utilizing proper optimal controls. Our work in this paper paves the way towards this user-centered information diffusion framework.","PeriodicalId":52145,"journal":{"name":"Computational Social Networks","volume":"2 1","pages":"18"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40649-015-0025-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35754748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Cascade source inference in networks: a Markov chain Monte Carlo approach. 网络中的级联源推理:一种马尔可夫链蒙特卡罗方法。

Computational Social Networks Pub Date : 2015-01-01 Epub Date: 2015-10-19 DOI: 10.1186/s40649-015-0017-4

Xuming Zhai, Weili Wu, Wen Xu

引用次数: 6

Network characteristics emerging from agent interactions in balanced distributed system. 平衡分布式系统中agent交互产生的网络特征。

Computational Social Networks Pub Date : 2015-01-01 Epub Date: 2015-07-15 DOI: 10.1186/s40649-015-0019-2

Mahdi Abed Salman, Cyrille Bertelle, Eric Sanlaville

{"title":"Network characteristics emerging from agent interactions in balanced distributed system.","authors":"Mahdi Abed Salman, Cyrille Bertelle, Eric Sanlaville","doi":"10.1186/s40649-015-0019-2","DOIUrl":"https://doi.org/10.1186/s40649-015-0019-2","url":null,"abstract":"A distributed computing system behaves like a complex network, the interactions between nodes being essential information exchanges and migrations of jobs or services to execute. These actions are performed by software agents, which behave like the members of social networks, cooperating and competing to obtain knowledge and services. The load balancing consists in distributing the load evenly between system nodes. It aims at enhancing the resource usage. A load balancing strategy specifies scenarios for the cooperation. Its efficiency depends on quantity, accuracy, and distribution of available information. Nevertheless, the distribution of information on the nodes, together with the initial network structure, may create different logical network structures. In this paper, different load balancing strategies are tested on different network structures using a simulation. The four tested strategies are able to distribute evenly the load so that the system reaches a steady state (the mean response time of the jobs is constant), but it is shown that a given strategy indeed behaves differently according to structural parameters and information spreading. Such a study, devoted to distributed computing systems (DCSs), can be useful to understand and drive the behavior of other complex systems.","PeriodicalId":52145,"journal":{"name":"Computational Social Networks","volume":"2 1","pages":"10"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40649-015-0019-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35678313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Analyzing the longitudinal impact of proximity, location, and personality on smartphone usage 分析距离、位置和个性对智能手机使用的纵向影响

Computational Social Networks Pub Date : 2014-12-01 DOI: 10.1186/s40649-014-0006-z

L. Meng, Shu Liu, A. Striegel

引用次数: 13

A partner-matching framework for social activity communities 社会活动社区的伙伴匹配框架

Computational Social Networks Pub Date : 2014-12-01 DOI: 10.1186/s40649-014-0005-0

Chunyu Ai, Wei Zhong, Mingyuan Yan, Feng Gu

引用次数: 7

Polarization of coalitions in an agent-based model of political discourse 基于主体的政治话语模型中的联盟极化

Computational Social Networks Pub Date : 2014-12-01 DOI: 10.1186/s40649-014-0007-y

Philip Leifeld

引用次数: 23

Influence-based community partition for social networks 基于影响力的社交网络社区划分

Computational Social Networks Pub Date : 2014-10-15 DOI: 10.1186/s40649-014-0001-4

Zaixin Lu, Yuqing Zhu, Wei Li, Weili Wu, Xiuzhen Cheng

引用次数: 2