  The goal of the ranking problem in networks is to rank nodes from best to
worst, according to a chosen criterion. In this work, we focus on ranking the
nodes according to their quality. The problem of ranking the nodes in bipartite
networks is valuable for many real-world applications. For instance,
high-quality products can be promoted on an online shop or highly reputed
restaurants attract more people on venues review platforms. However, many
classical ranking algorithms share a common drawback: they tend to rank older
movies higher than newer movies, though some newer movies may have a high
quality. This time bias originates from the fact that older nodes in a network
tend to have more connections than newer ones. In the study, we develop a
ranking method using a rebalance approach to diminish the time bias of the
rankings in bipartite graphs.
