论文标题
基于消息分布的社交网络中社区检测的一种新方法
A new method for community detection in social networks based on message distribution
论文作者
论文摘要
社交网络是由人及其关系组成的社会结构，如今，在数据扩展中起着重要作用。在这样的网络中，社区被认为是经常相互互动的用户组。在本文中，将引入一种供社区检测的方法，该方法具有与不同种类的社交网络的采用能力，并且与实际世界同步。本文中最重要的定义参数之一是网络节点之间传输的消息的速率，将动态研究此参数。在此策略中，网络以不同的时间间隔进行审查，并增强或削弱了节点之间的关系。因此，网络的拓扑是响应用户的行为而不断变化。所提出的算法中的定义参数能够采用不同类型的社交网络，将重量分配给每个参数，这表明该参数与其他参数相对重要。获得的结果表明，与类似方法相比，该方法可实现理想的结果。
Social networks are the social structures which are composed of people and their relationships and nowadays, play an important role in data extension. In such networks, the communities are recognized as the groups of users who are often interacting with each other. In this article, a method will be introduced for community detection, which has the capability of adoption with different kinds of social networks and also is synchronized with the actual world. One of the most important defined parameters in this paper is the rate of the transferred messages between the nodes of the network, this parameter would be dynamically investigated. In this strategy, the network is reviewed in different time intervals, and the inter-node relations are enhanced or weakened. Therefore, the topology of the network is continuously changing in response to the behavior of the users. The defined parameters in the proposed algorithm are capable of adopting with different types of the social networks and a weight will be assigned to every parameter which is indicative of the relative importance of that parameter in comparison with the other ones. The obtained results show that this method, in comparison with the similar methods, leads to achievement of the desirable results.
