Abstract
Within social networking services, users construct their personal social networks by creating asymmetric or symmetric social links. They usually follow friends and selected famous entities, such as celebrities and news agencies. On such platforms, attention is used as currency to consume the information. In this chapter, we investigate how users follow famous entities. We analyze the static and dynamical data within a large social networking service with a manually classified set of famous entities. The results show that the in-degree of famous entities does not fit to a power-law distribution. Conversely, the maximum number of famous followees in one category for each user shows a power-law property. Finally, in an attention economics perspective, we discuss the reasons underlying these phenomena. These findings might be helpful in microblogging marketing and user classification.
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We appreciate Tencent Inc, the organizers of KDD Cup 2012, for sharing the datasets of microblogging service with the public.
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Yu, S., Kak, S. (2014). Social Network Dynamics: An Attention Economics Perspective. In: Pedrycz, W., Chen, SM. (eds) Social Networks: A Framework of Computational Intelligence. Studies in Computational Intelligence, vol 526. Springer, Cham. https://doi.org/10.1007/978-3-319-02993-1_11
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DOI: https://doi.org/10.1007/978-3-319-02993-1_11
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