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Analysis and mining of social media has become an important research area. A challenging problem in this area consists in the identification of a group of users with similar patterns. In this paper, we propose the classification of users based on their activity profiles (e.g., periods of the day when the user is most and least active in online communications). Activity profiles can be useful for many...
Community detection and influence analysis are significant notions in social networks. We exploit the implicit knowledge of influence-based connectivity and proximity encoded in the network topology, and propose a novel algorithm for both community detection and influence ranking. Using a new influence cascade model, the algorithm generates an influence vector for each node, which captures in detail...
The entity disambiguation task partitions the records belonging to multiple persons with the objective that each decomposed partition is composed of records of a unique person. Existing solutions to this task use either biographical attributes, or auxiliary features that are collected from external sources, such as Wikipedia. However, for many scenarios, such auxiliary features are not available,...
Community detection is one of the most important problems in social network analysis in the context of the structure of the underlying graphs. Many researchers have proposed their own methods for discovering dense regions in social networks. Such methods are only designed with links of the underlying social network. However, with the development of recent applications, rich edge content can be available...
In recent years, cross-site scripting attacking usually occurred on the social networks. The attackers hide the malicious script codes in web links, and easily get personal sensitive information if someone clicks these links. This article firstly analyzes the characteristics of the social network topology and the relationships of network users, and then establishes the worm propagation model in order...
Building non-trivial software is a social endeavor. Therefore, understanding the social network of developers is key to the study of software development organizations. We present a graph representation of the commit behavior of developers within the Apache Software Foundation for 2010 and 2011. Relationships between developers in the network represent collaborative commit behavior. Several similarity...
Social behaviors such as dining preferences are inextricably linked with physical social locations (e.g., home, work, and hangout location), rather than just due to the personal interests/cultures and influences from social peers. With the uses of location-based services in online social networks over smart phones, such physical social locations are easily available as an effective alternative to...
Trustworthy degree plays an important role in the quantity analysis of trustworthy networks. In this paper, we use mean 2-form of vector to compute the trustworthy degree. Some algebraic properties are discussed. To clarify the reasonability of this method, a simple simulation is constructed.
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