This paper introduces a new approach to detecting scientists’ field mobility by focusing on an author’s self-citation network,
and the co-authorships and keywords in self-citing articles. Contrary to much previous literature on self-citations, we will
show that author’s self-citation patterns reveal important information on the development and emergence of new research topics
over time. More specifically, we will discuss self-citations as a means to detect scientists’ field mobility. We introduce
a network based definition of field mobility, using the Optimal Percolation Method (Lambiotte & Ausloos, 2005; 2006). The results of the study can be extended to selfcitation networks of groups of authors and, generally also
for other types of networks.