  Using percentile shares, one can visualize and analyze the skewness in
bibliometric data across disciplines and over time. The resulting figures can
be intuitively interpreted and are more suitable for detailed analysis of the
effects of independent and control variables on distributions than regression
analysis. We show this by using percentile shares to analyze so-called "factors
influencing citation impact" (FICs; e.g., the impact factor of the publishing
journal) across year and disciplines. All articles (n= 2,961,789) covered by
WoS in 1990 (n= 637,301), 2000 (n= 919,485), and 2010 (n= 1,405,003) are used.
In 2010, nearly half of the citation impact is accounted for by the 10%
most-frequently cited papers; the skewness is largest in the humanities (68.5%
in the top-10% layer) and lowest in agricultural sciences (40.6%). The
comparison of the effects of the different FICs (the number of cited
references, number of authors, number of pages, and JIF) on citation impact
shows that JIF has indeed the strongest correlations with the citation scores.
However, the correlation between FICs and citation impact is lower, if
citations are normalized instead of using raw citation counts.
