  Reference Publication Year Spectroscopy (RPYS) has been developed for
identifying the cited references (CRs) with the greatest influence in a given
paper set (mostly sets of papers on certain topics or fields). The program
CRExplorer (see www.crexplorer.net) was specifically developed by Thor, Marx,
Leydesdorff, and Bornmann (2016a, 2016b) for applying RPYS to publication sets
downloaded from Scopus or Web of Science. In this study, we present some
advanced methods which have been newly developed for CRExplorer. These methods
are able to identify and characterize the CRs which have been influential
across a longer period (many citing years). The new methods are demonstrated in
this study using all the papers published in Scientometrics between 1978 and
2016. The indicators N_TOP50, N_TOP25, and N_TOP10 can be used to identify
those CRs which belong to the 50%, 25%, or 10% most frequently cited
publications (CRs) over many citing publication years. In the Scientometrics
dataset, for example, Lotka's (1926) paper on the distribution of scientific
productivity belongs to the top 10% publications (CRs) in 36 citing years.
Furthermore, the new version of CRExplorer analyzes the impact sequence of CRs
across citing years. CRs can have below average (-), average (0), or above
average (+) impact in citing years (whereby average is meant in the sense of
expected values). The sequence (e.g. 00++---0--00) is used by the program to
identify papers with typical impact distributions. For example, CRs can have
early, but not late impact ("hot papers", e.g. +++---) or vice versa ("sleeping
beauties", e.g. ---0000---++).
