Human Flesh Search (HFS), originated in China, has become an explosive Web phenomenon. HFS episodes typically start with news events. Participants pay close attention to the events, get together online, investigate, try to solve the real world problems and find the truth. In HFS episodes, participants form online communities, share information and collaborate with each other. Such online communities are unique subjects of social network study. This dissertation presents the first systematic empirical study and data-driven modeling of HFS. We give the formal definition of HFS, summarize the typical HFS process and classify the episodes based on their topics. We study network measurements of the social networks corresponding to the communities of individual HFS episodes. The communities are strongly centralized, and have small world property. Information diffusion within the communities restricts by the central hubs of the networks. To understand the overall properties of HFS communities, HFS core network is built to study the connections of participants in all episodes. The result shows that HFS core network is a small world and scale-free network. Since the HFS communities do not follow any existing network model, a modified network model is purposed to explain the characteristics of HFS episode networks.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/243119 |
| Date | January 2012 |
| Creators | Feng, Zhuo |
| Contributors | Zeng, Daniel, Lin, Weihua, Liu, Jian, Lin, Weihua |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | text, Electronic Dissertation |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
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