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Modeling and measuring social influence is a major problem in Social Network Analysis. Existing models and methods could handle individual influence analysis conveniently, but they rarely estimate the social influence of communities which are ubiquitous in social networks. Based on the structures of online social networks, a community oriented influence analysis model is proposed. Then, we provide...
Multi-label classification in social network environments is becoming a key area of data mining research in recent years. Given some nodes' labels (i.e., the sources), the task is to infer some other nodes' labels (i.e., the targets) in the same network. Relational classification methods, which leverage the correlation of labels between linked instances, have been shown to outperform traditional classifiers...
Hierarchical agglomerative algorithm is widespread used in community detection of social networks. This paper explores an enhanced similarity which is based on interactive behavior of social members. The enhanced similarity expands the concept of similarity from vertexes to communities in the social network. Furthermore, the hierarchical agglomerative algorithm has been applied and the enhanced similarity...
With the development of Social Networking Services, users can publish and receive information expediently. With the scale of information to be processed is becoming bigger, the information acquisition rules adopted by traditional search engine met with many difficulties. To solve the problem, we must develop new UGC collection strategy. We think there are three main factors: user, UGC and the interactive...
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