Correction: Research topic flows in co‑authorship networks

Predicting Links in Large Coauthorship Networks

Coauthorship networks and academic literature recommendation

Recommender systems are increasingly touted as an indispensable service of many online stores and websites. Most existing recommendation techniques typically rely on users’ historical, long-term interest profiles, derived either explicitly from users’ preference ratings or implicitly from their purchasing/ browsing history, to arrive at recommendation decisions. In this study, we propose a coau...

Coauthorship networks and patterns of scientific collaboration.

By using data from three bibliographic databases in biology, physics, and mathematics, respectively, networks are constructed in which the nodes are scientists, and two scientists are connected if they have coauthored a paper. We use these networks to answer a broad variety of questions about collaboration patterns, such as the numbers of papers authors write, how many people they write them wi...

Coauthorship and citation networks for statisticians: Comment

Analyses of coauthorship and citation networks offer a fertile ground for studying research and collaboration patterns of scientific communities. Ji and Jin’s efforts of collecting, cleaning and summarizing in various ways citation and coauthorship networks for statisticians is a great step forward to provide the community with a first such data set for self-study. They perform several descript...

A topological analysis of scientific coauthorship networks

We study coauthorship networks based on the preprints submitted to the Los Alamos cond-mat database during the period 2000–2005. In our approach two scientists are considered connected if they have coauthored one or more cond-mat preprints together in the same year. We focus on the characterization of the structural properties of the derived graphs and on the time evolution of such properties. ...