The scientific impact of an individual is measured by the citation count of their articles. Several citation-based indices and centrality measures are present for the evaluation of scientific impact of individual. In the research community, generally every author gets full credit of citation count of an article, but rarely their contribution is equal. To resolve this issue, we used the Poisson distribution to distribute the share credit of authors in multi-authored article and for evaluation of scientific impact of an individual, the eigenvector centrality has been used. In centrality measures, the eigenvector centrality is a good measure to evaluate the scientific impact of individual, because it uses the scientific impact of collaborators as well as the collaborators of collaborated researchers. For calculation of eigenvector centrality, first we set that the initial amount of influence of every node (author) is the total number of normalized citation count and the collaboration weight is the correlation coefficient based on individual normalized citation count. To validate the proposed method, an experimental analysis has been done on the collaboration network of 186007 scholars. © Springer Nature Singapore Pte Ltd. 2019