  We explore if and how Microsoft Academic (MA) could be used for bibliometric
analyses. First, we examine the Academic Knowledge API (AK API), an interface
to access MA data, and compare it to Google Scholar (GS). Second, we perform a
comparative citation analysis of researchers by normalizing data from MA and
Scopus. We find that MA offers structured and rich metadata, which facilitates
data retrieval, handling and processing. In addition, the AK API allows
retrieving frequency distributions of citations. We consider these features to
be a major advantage of MA over GS. However, we identify four main limitations
regarding the available metadata. First, MA does not provide the document type
of a publication. Second, the 'fields of study' are dynamic, too specific and
field hierarchies are incoherent. Third, some publications are assigned to
incorrect years. Fourth, the metadata of some publications did not include all
authors. Nevertheless, we show that an average-based indicator (i.e. the
journal normalized citation score; JNCS) as well as a distribution-based
indicator (i.e. percentile rank classes; PR classes) can be calculated with
relative ease using MA. Hence, normalization of citation counts is feasible
with MA. The citation analyses in MA and Scopus yield uniform results. The JNCS
and the PR classes are similar in both databases, and, as a consequence, the
evaluation of the researchers' publication impact is congruent in MA and
Scopus. Given the fast development in the last year, we postulate that MA has
the potential to be used for full-fledged bibliometric analyses.
