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Social media has become an important platform for people to express opinions, share information and communicate with others. Detecting and tracking topics from social media can help people grasp essential information and facilitate many security-related applications. As social media texts are usually short, traditional topic evolution models built based on LDA or HDP often suffer from the data sparsity...
With the continuous development of social networking sites, the volume of social media data has exploded and the user-generated content is becoming more and more diverse. As a result, the modality of massive social media data is no longer confined to the single text mode. This brings new challenges to social media analytics in general and its examplar field such as sentiment analysis in particular...
Online interactions, especially user generated contents on social events, reveal a variety of communicative purposes ranging from expressing feelings to proposing suggestions. Recognizing intents in users' online interactive behavior from massive social media data can effectively identify users' motives and intents behind communication and provide important information to aid monitoring, analysis...
Social networking sites provide a convenient way for users to participate in discussion groups and communicate with others. While users situate in and enjoy such a social environment, it is important for various security related applications to understand, model and analyze participating users' behavior. In this paper, we make an attempt to model and predict user participation behavior in discussion...
The cyber-physical-social systems (CPSS) provide an ideal paradigm for the design and construction of command and control organization. This article presents the concept of a CPSS for command and control and discusses its operational process and self-synchronization mechanism in CPSS.
In recent years, social behavioral data have been exponentially expanding due to the tremendous success of various outlets on the social Web (aka Web 2.0) such as Facebook, Digg, Twitter, Wikipedia, and Delicious. As a result, there's a need for social learning to support the discovery, analysis, and modeling of human social behavioral data. The goal is to discover social intelligence, which encompasses...
Cultural modeling is an emergent and promising research area in social computing. It aims to develop behavioral models of groups and analyze the impact of culture factors on group behavior using computational methods. Classification methods play a critical role in cultural modeling domain. As various cultural-related datasets possess different properties, for group behavior prediction, it is important...
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