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| Research on Collaborative Tagging Behavior Mechanisms Based on Collective Intelligence Theory Based on Douban Movie Tag Data |
| Yi Ming1, Feng Cuicui1, Mo Fuchuan1, Deng Weihua2 |
1.School of Information Management, Central China Normal University, Wuhan 430079
2.School of Public Management, Huazhong Agricultural University, Wuhan 430070 |
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Abstract Based on the theory of collective intelligence, this study constructed a collaborative tagging behavior model. The collaborative tagging behavior included three sub-processes: the initial stage, intermediate stage, and ultimate stage at the macro level, and three sub-steps: divergence, convergence, and cohesion at the micro level. The macro level described the process of collaborative information organization behavior from quantitative change to qualitative change, highlighting the process of collaborative tagging behavior; and the micro level described the basic process of the emergence of group intelligence in collaborative tagging behavior, highlighting the synergy of collaborative tagging behavior. Empirical analysis based on Douban movie tag data found that the collaborative tagging behavior model reasonably explained the process and synergy of collaborative tagging behavior. The skew coefficient of tag labeling times generally increased, and the collective intelligence kept emerging during the process of collaborative tagging behavior. Tag citation was the normal status of the entire collaborative tagging behavior process, leading to the formation of a stable, high-frequency tag group that represented the opinions of the group users. The eight patterns of collaborative tagging behavior occurred throughout the entire process of collaborative tagging behavior, but the convergence mode was relatively stable, and the divergence mode will join the convergence mode with high probability. The collaborative tagging behavior process was dominated by convergence, which showed that the group users’ opinions made a transition from divergence to convergence, and finally condensed to achieve a global consensus. The results showed that the theoretical model and research methods of this paper are scientific, and can enrich the theory and method of collaborative information behavior.
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Received: 16 February 2020
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