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The spread and diffusion of information has become one of the hot issues in today’s social network analysis. To analyze the spread of online social network information and the attribute of cascade, in this paper, we discuss the spread of two kinds of users’ decisions for city-wide activities, namely the “want to take part in the activity” and “be interested in the activity”, based on the users’ attention...
Overlapping community detection algorithm research is one of hot topics in current social network analysis. In this paper, we applied the idea of weighted label propagation to overlapping community detection algorithm design, and propose a weighted label propagation algorithm (WLPA). Moreover, in order to evaluate the performance results of various overlapping community detection algorithms, we put...
In the past few years, social networks became extremely popular all over the globe. With more than one billion users worldwide, social networks are considered the new venue of innovation over the Internet. Through social networks, people can start and do business, or simply meet and maintain contact with other persons. However, due to its rapid growth, it has become common that users want to create...
With the proliferation of high-end mobile devices that feature wireless interfaces, many promising applications are enabled in opportunistic networks. In contrary to traditional networks, opportunistic networks utilize the mobility of nodes to relay messages in a store-carry-forward paradigm. Thus, the relay process in opportunistic networks faces several practical challenges in terms of delay and...
Deeper knowledge of social networks' structure and temporal evolution enhances data mining for both research and education purposes. An empirical analysis of a Chinese social network, Renren, shows that it follows an exponentially truncated power law in degree distribution, and has a short average node distance.
What patterns do non-giant connected components in a graph or network have? How do the non-giant connected components behave during their evolution over time? How can we model the time-evolving patterns of non-giant connected components? These questions are important for understanding the evolution of social networks, but they were seldom studied in previous work, which focused mainly on the giant...
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