  Over the recent years, there has been a growing interest in developing new
research evaluation methods that could go beyond the traditional citation-based
metrics. This interest is motivated on one side by the wider availability or
even emergence of new information evidencing research performance, such as
article downloads, views and Twitter mentions, and on the other side by the
continued frustrations and problems surrounding the application of purely
citation-based metrics to evaluate research performance in practice.
Semantometrics are a new class of research evaluation metrics which build on
the premise that full-text is needed to assess the value of a publication. This
paper reports on the analysis carried out with the aim to investigate the
properties of the semantometric contribution measure, which uses semantic
similarity of publications to estimate research contribution, and provides a
comparative study of the contribution measure with traditional bibliometric
measures based on citation counting.
