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the existing information diffusion models focus on analyzing the spatial distribution of certain pieces of messages in social networks. However, these conventional models ignored another important characteristic of diffusion: gradually changing of message contents due to the 'new' and 'comment' mechanisms. A novel genetic-algorithm-based information evolution model is proposed to reproduce both the...
The conventional algorithm (COPRA -- Community Overlap PRopagation Algorithm) proposed by Steve Gregory is efficient and useful in Complex Networks, but it is a challenge to select a suitable parameter "thr" as the input of the algorithm. In this paper, we put forward a threshold based label propagation algorithm, in which each vertex in the network is identified with a threshold respectively,...
In this paper we propose two algorithms for overlapping community detection based on neighborhood vector propagation algorithm(NVPA), a community detection algorithm which can detect disjoint communities with high accuracy. The first algorithm is named Link Partition of Overlapping Communities (LPOC). In this algorithm, we first convert a node graph to a link graph, then we use NVPA to find the communities...
The spreading process of rumor is different from that of general messages because two special factors: reason of individual and rumor refuting, affect the process of rumor dissemination besides conventional factor, i.e. information amount. In this paper, we propose a genetics-based rumor diffusion model (GRDM) which regards an individual with multiple rumors in a network as a ‘chromosome’ which is...
Social Peer-to-Peer (P2P) is a novel model to organize sensor networks, which can establish social relationships in an autonomous way with the benefits of extending the network boundaries and enhancing the network scalability. However, the complexity and time dependence characteristics introduced by social P2P model raise difficulties for assessing and selecting security services accurately and effectively...
Many algorithms have been designed to detect community structure in social networks. However, most algorithms can only detect disjoint communities effectively. A new overlapping community structure detecting algorithm is proposed in this paper, which adopts modularity to community clustering. In order to evaluate the algorithm, Modularity by Newman and the NMI (Normalized Mutual Information) by Lancichinetti...
Study on diffusion behaviors, such as contagion of virus, adoption of production, and information propagation, is one of the hottest topics of social network research. The conventional models usually focus on a particular factor that influences the contagion process. A novel model of diffusion based on multiple behavior evidence fusion is proposed on the analysis of prevalent social network data set,...
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