This paper studies the problem of identifying influencers on specific topics in the microblog sphere. Prior works usually use the cumulative number of social links to measure users' topic level influence, which ignores the dynamics of influence. As a result, they usually find faded influencers. To address the limitations of prior methods, we propose a novel probabilistic generative model to capture the variation of influence over time. Then a influence decay method is proposed to measure users' current topic-level influence.
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