Knowledge on the move: Reconstructing scientists' mobility network

When standard network measures fail to rank journals: A theoretical and empirical analysis

Quantifying and suppressing ranking bias in a large citation network

Citation counts for papers from different fields can't be compared directly because they adopt different citation practices. Researchers have proposed various procedures to suppress these biases, but a new statistical framework shows that existing indicators, including the relative citation count, are still biased by paper field and age. A new normalization procedure motivated by the z-score produces much less biased rankings when applied to citation count and PageRank score. The problem of achieving an ideal unbiased ranking of publications remains open.

Knowledge in socio-economic systems - Insights from collaboration, mobility, and data-driven models