The Eigenfactor is a journal metric, which was developed by Bergstrom and his colleagues at the University of Washington. They invented the Eigenfactor as a response to the criticism against the use of simple citation counts. The Eigenfactor makes use of the network structure of citations, i.e. citations between journals, and establishes the importance, influence or impact of a journal based on its location in a network of journals. The importance is defined based on the number of citations between journals. As such, the Eigenfactor algorithm is based on Eigenvector centrality. While journal-based metrics have been criticized, the Eigenfactor has also been suggested as an alternative in the widely used San Francisco Declaration on Research Assessment (DORA).

翻译：“Eigenfactor”是Bergstrom及其在华盛顿大学的同事开发的期刊指标,他们发明了“Eigenfactor”,作为对批评使用简单的引用计数的批评的回应。“Eigenfactor”利用了引用的网络结构,即期刊之间的引文结构,根据期刊在期刊网络中的位置,确定了期刊的重要性、影响或影响。《Eigenfactor》的重要性是根据期刊之间的引文数量界定的。因此,“Eigenfactor”算法以“Eigenvictor中心”为基础。尽管以日记为基础的计量标准受到批评,但“Eigenfactor”也作为广泛使用的《旧金山研究评估宣言》(DORA)中的一种替代方法。