会议名称(中文)： 第一届国际网络动力学研讨会
会议名称(英文)： 1st International Workshop on Dynamics in Networks (DyNo2015)
所属学科： 一般力学与力学基础,计算机网络
开始日期： 2015-08-25
结束日期： 2015-08-28
所在国家： 法国
所在城市： 法国
具体地点： Paris, France
主办单位： IEEE Computer Society ACM SIGKDD
[ 重要日期 ]
全文截稿日期： 2015-05-15
[ 会务组联系方式 ]
联系人： Giulio Rossetti
会议背景介绍：
In the last years we witnessed to a shift from static network analysis to a dynamic networks analysis, i.e., the study of networks whose structure change over time. As time goes by, all the perturbations which occur on the network topology due to the rise and fall of nodes and edges have repercussions on the network phenomena we are used to observe. As an example, evolution over time of social interactions in a network can play an important role in the diffusion of an infectious disease.
Nowadays, one of the most fascinating challenges is to analyze the structural dynamics of real world networks and how they impact on the processes which occurs on them, i.e. the spreading of social influence and diffusion of innovations. Results in this field will enable for a better understanding of important aspects of human behaviors as well as to a more detailed characterization of the complex interconnected society we inhabit. Since the last decades, diffusive and spreading phenomena were facilitated by the enormous popularity of the Internet and the evolution of social media that enable an unprecedented exchange of information. For this reason, understanding how social relationships unravel in these rapidly evolving contexts represents one of the most intriguing field of research ever.
The purpose of this workshop is to encourage principled research that will lead to the advancement of the social science in time-evolving networks. The workshop will seek top- quality submissions addressing important topics such as: dynamic network modeling, time- aware network mining approaches, social influence spreading, diffusion processes in dynamic networks and forecast of network topology perturbation.
征文范围及要求：
Topics of interest to the workshop include, but are not limited to, the following:
– Temporal network modeling
– Dynamic Social Network Analysis
– Dynamical processes on temporal networks
– Social Prominence and Influence maximization
– Diffusion of information and innovations
– Epidemic models on graphs
– Evolutionary Community Discovery
– Time-aware Link Prediction
– Dynamic network generative models
– Multiplex network dynamics |
