Modeling Affinity based Popularity Dynamics.
CIKM(2017)
摘要
Information items draw collective attention across a heterogeneous social system, leading to great disparities of popularity. Unveiling underlying diffusion processes is very challenging, since a social system consists of time-evolving subgroups interacting and exerting disproportionate influences on an individual item's popularity. In this study, we propose the Affinity Poisson Process model (APP) which models popularity dynamics, by incorporating (1) affinities between subgroups, (2) heterogeneous preferential attachment, and (3) subgroup-level time decay. As a case study, we apply our proposed model to scholarly publications in computer science. Our model outperforms the state of the art approach in predicting citation volumes of individual papers. More importantly, the proposed model enables us to uncover popularity dynamics driven by intra- and inter-subgroup interactions, which has been neglected in prior work. We expect that our model can afford interpretable insights on the attention economy in terms of affinity and aging effect.
更多查看译文
关键词
Affinity, popularity dynamics, interdisciplinary citations
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络