Modeling And Analysis Of Organization And Collaboration In Human Flesh Search

In this paper, the human flesh search, a typical cyber-enabled social movement organizations were studied. Human flesh search, originated at the beginning of this century, is a social phenomenon from the Internet which mainly happened in China. It was an explosive Web phenomenon several years ago. Some famous human flesh search episodes happened at that time, such as South China Tiger. Although the human flesh search often been associated with negtive news at that time, such as violence etc., it also began to play an important role in some area, such as finding relatives after earthquake, anti-corruption etc. Actually, Human flesh search is a typical mass collaboration phenomenon. The episodes provide valuable material for study of mass collaboration.human flesh search happens everyday in our daily life now. This paper takes the human flesh search, the large-scale collaborative phenomenon, as the research target. We collected more than 10 thousand human flesh search episodes, which participanted by about 3 million Internet users. More than 4 million messages were analyzed to study the human flesh search phenomenon from empirical and theoretical research.This paper presents systematical empirical study and data-driven modeling of human flesh search. We give the formal definition of human flesh search, summarize the typical human flesh search process and classify the episodes based on their topics. We study network measurements of the social networks corresponding to the communities of individual human flesh search episodes.For the human flesh search community, this article studies the basic features of human flesh search network groups, analyzes the structure, the role of members in this group, established social network between the participants. Through the empirical data analysis, we found that this group in different roles have very different attributes, the human flesh search tasks often published by the participants with strong media properties, and players often are grassroots. In this groups, only about 0.3% of members often participated in several episodes, they are a relatively stable organization. They linked very close, but there is no authoritative affiliation between them. It is a closely linked but strongly distributed organization.Based on the analysis results of the group’s community structure, this paper studies the organizational collaboration mechanism between the group members in the search process. Through the analysis of the propagation process of human flesh search and collaboration process of the episodes, we found that the members behind human flesh search episodes is not a random organization, in fact, the collaborative process of human flesh search has many rules to follow.Based on the results of empirical analysis, we proposed an artificial society model based on resource mobilization, and established relevant agent model and organization model based on the mobilization of human flesh search. The collaboration mechanism were analyzed, and the mobilization of human flesh search organization algorithm was designed, the model was verified by real data, the simulated results shown that the model can simulate the human flesh search collaboration network between participants and the process of collaborations.Through the above analysis and modeling of human flesh search, this paper analyzed the factors of human flesh search results, and based on these factors to predict the results of human flesh search. Results show that the search results in a certain extent can be predicted.These findings uncovered the mask of large-scale Internet user’s collaboration and mobilization. It provided some meaningful directions and a starting point for further research on swarm intelligence and network related works. We hope that more research based on real data can get the attention of scholars, especially from sociology, anthropology, network science, computer science, statistical physics, and control theory etc. Cross multidisciplinary collaboration will greatly promote the research, help people get a better understanding of the complex system of mass collaboration, promote mass collaboration to create a more brilliant civilization.