Uncovering Diffusion in Academic Publications using Model-Driven and Model-Free Approaches
Information spreads across heterogeneous social systems, and the underlying network structures are hard to collect or define. The goal of this paper is to estimate macro-level information diffusion using time-series activity sequences of heterogeneous populations without the need to know detailed network structures. We propose a consistent way of understanding dynamic influence among populations with both model-driven and model-free approaches. As a real-word example, we focus on computer...[Show more]
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