Abstract Recent years have witnessed increased interests in measuring authority and modelling in?uence in social networks. For a long time, PageRank has been widely used for authority computation and has also been adopted as a solid baseline for evaluating social in?uence related applications. However, the connection between authority measurement and in?uence modelling is not clearly established. To this end, in this paper, we provide a focused study on understanding of PageRank as well as the relationship between PageRank and social in?uence analysis. Along this line, we ?rst propose a linear social in?uence model and reveal that this model is essentially PageRank with prior. Also, we show that the authority computation by PageRank can be enhanced with more generalized priors. Moreover, to deal with the computational challenge of PageRank with general priors, we provide an upper bound for top authoritative nodes identi?cation. Finally, the experimental results on the scienti?c collaboration network validate the effectiveness of the proposed social in?uence model.