  In this paper, we propose a measure to assess scientific impact that
discounts self-citations and does not require any prior knowledge on the their
distribution among publications. This index can be applied to both researchers
and journals. In particular, we show that it fills the gap of h-index and
similar measures that do not take into account the effect of self-citations for
authors or journals impact evaluation. The paper provides with two real-world
examples: in the former, we evaluate the research impact of the most productive
scholars in Computer Science (according to DBLP); in the latter, we revisit the
impact of the journals ranked in the 'Computer Science Applications' section of
SCImago. We observe how self-citations, in many cases, affect the rankings
obtained according to different measures (including h-index and ch-index), and
show how the proposed measure mitigates this effect.
