On spreading recommendations via social gossip
Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures
Towards understanding: a study of the SourceForge.net community using modeling and simulation
SpringSim '07 Proceedings of the 2007 spring simulation multiconference - Volume 2
Blogosphere: research issues, tools, and applications
ACM SIGKDD Explorations Newsletter
Collective Intelligence in Action
Collective Intelligence in Action
Towards a model of understanding social search
Proceedings of the 2008 ACM conference on Computer supported cooperative work
Simulation of scale-free networks
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
Knowledge Aggregation in Human Flesh Search
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
SUPE-Net: An Efficient Parallel Simulation Environment for Large-Scale Networked Social Dynamics
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
On social computing research collaboration patterns: a social network perspective
Frontiers of Computer Science in China
A study of human flesh search with epidemic models
Proceedings of the 3rd Annual ACM Web Science Conference
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With the development of on-line forum technology and the pervasive participation of the public, the Human Flesh Search is becoming an arising phenomenon which makes a great impact on our daily life. There arose big research interests in social, legal issues resulted from HFS, however, very little work has been conducted to understand how it comes into being and how it dynamically evolves. This paper proposes a modeling and simulation approach incorporating network expansion and GOSSIP propagation with feedback for a better understanding of the human flesh search phenomenon. Based on the acquisition and analysis of the netizens’ surfing behavior data, the evolution of the HFS is modeled as a network growth processwith proper dynamic input, which is characterized by heavy-tail and burst-oriented distribution, modeling as a Weibulloid process. Then, an improved GOSSIP model with feedback is proposed to represent the information propagation, processing and aggregation during the HFS. New insights for HFS are gained through a set of simulation experiments.