  Google's PageRank has created a new synergy to information retrieval for a
better ranking of Web pages. It ranks documents depending on the topology of
the graphs and the weights of the nodes. PageRank has significantly advanced
the field of information retrieval and keeps Google ahead of competitors in the
search engine market. It has been deployed in bibliometrics to evaluate
research impact, yet few of these studies focus on the important impact of the
damping factor (d) for ranking purposes. This paper studies how varied damping
factors in the PageRank algorithm can provide additional insight into the
ranking of authors in an author co-citation network. Furthermore, we propose
weighted PageRank algorithms. We select 108 most highly cited authors in the
information retrieval (IR) area from the 1970s to 2008 to form the author
co-citation network. We calculate the ranks of these 108 authors based on
PageRank with damping factor ranging from 0.05 to 0.95. In order to test the
relationship between these different measures, we compare PageRank and weighted
PageRank results with the citation ranking, h-index, and centrality measures.
We found that in our author co-citation network, citation rank is highly
correlated with PageRank's with different damping factors and also with
different PageRank algorithms; citation rank and PageRank are not significantly
correlated with centrality measures; and h-index is not significantly
correlated with centrality measures.
