One commonly used method in author co-citation analysis is
factor analysis, which has been applied to analyze the essential
dimensionality of the given co-citation data in a subject domain.
The study of [63] demonstrates the author co-citation analysis of
the information science field and shows that some authors do indeed
simultaneously belong to several specialties. The co-citation
relationships between authors are usually represented by a cocitation
matrix, which serves as an input of the factor analysis.
The co-citation matrix computes a correlation matrix of Pearson
correlation coefficients, which can be used as a measure of similarity
between pairs of authors. Pathfinder network (PFNET) scaling is
used to prune the network defined by the correlation matrix [61].
The study by Chen and Steven [12] applies PFNET scaling to extract
the most important relationships from the correlation matrix.