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During Eugene Garfield's (EG's) lengthy career as information scientist, he published about 1500 papers. In this study, we use the impressive oeuvre of EG to introduce a new type of bibliometric networks: keyword co-occurrences networks based on the context of citations, which are referenced in a certain paper set (here: the papers published by EG). The citation context is defined by the words which are located around a specific citation. We retrieved the citation context from Microsoft Academic. To interpret and compare the results of the new network type, we generated two further networks: cooccurrence networks which are based on title and abstract keywords from (1) EG's papers and (2) the papers citing EG's publications. The comparison of the three networks suggests that papers of EG and citation contexts of papers citing EG are semantically more closely related to each other than to titles and abstracts of papers citing EG. This result accords with the use of citations in research evaluation that is based on the premise that citations reflect the cognitive influence of the cited on the citing publication.

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.

This is the first detailed study on the coverage of Microsoft Academic (MA). Based on the complete and verified publication list of a university, the coverage of MA was assessed and compared with two benchmark databases, Scopus and Web of Science (WoS), on the level of individual publications. Citation counts were analyzed, and issues related to data retrieval and data quality were examined. A Perl script was written to retrieve metadata from MA based on publication titles. The script is freely available on GitHub. We find that MA covers journal articles, working papers, and conference items to a substantial extent and indexes more document types than the benchmark databases (e.g., working papers, dissertations). MA clearly surpasses Scopus and WoS in covering book-related document types and conference items but falls slightly behind Scopus in journal articles. The coverage of MA is favorable for evaluative bibliometrics in most research fields, including economics/business, computer/information sciences, and mathematics. However, MA shows biases similar to Scopus and WoS with regard to the coverage of the humanities, non-English publications, and open-access publications. Rank correlations of citation counts are high between MA and the benchmark databases. We find that the publication year is correct for 89.5% of all publications and the number of authors is correct for 95.1% of the journal articles. Given the fast and ongoing development of MA, we conclude that MA is on the verge of becoming a bibliometric superpower. However, comprehensive studies on the quality of MA metadata are still lacking.

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This study presents humanities scholars' conceptions of research and subjective notions of quality in the three disciplines German literature studies, English literature studies, and art history, captured using 21 Repertory Grid interviews. We identified three dimensions that structure the scholars' conceptions of research: quality, time, and success. Further, the results revealed four types of research in the humanities: positively connoted 'traditional' research (characterized as individual, discipline-oriented, and ground-breaking research), positively connoted 'modern' research (cooperative, interdisciplinary, and socially relevant), negatively connoted 'traditional' research (isolated, reproductive, and conservative), and negatively connoted 'modern' research (career oriented, epigonal, calculated). In addition, 15 quality criteria for research in the three disciplines German literature studies, English literature studies, and art history were derived from the Repertory Grid interviews.

Research assessment in the social sciences and humanities (SSH) is delicate. Assessment procedures meet strong criticisms from SSH scholars and bibliometric research shows that the methods that are usually applied are ill-adapted to SSH research. While until recently research on assessment in the SSH disciplines focused on the deficiencies of the current assessment methods, we present some European initiatives that take a bottom-up approach. They focus on research practices in SSH and reflect on how to assess SSH research with its own approaches instead of applying and adjusting the methods developed for and in the natural and life sciences. This is an important development because we can learn from previous evaluation exercises that whenever scholars felt that assessment procedures were imposed in a top-down manner without proper adjustments to SSH research, it resulted in boycotts or resistance. Applying adequate evaluation methods not only helps foster a better valorization of SSH research within the research community, among policymakers and colleagues from the natural sciences, but it will also help society to better understand SSH's contributions to solving major societal challenges. Therefore, taking the time to encourage bottom-up evaluation initiatives should result in being able to better confront the main challenges facing modern society. This article is published as part of a collection on the future of research assessment.

The assessment of research performance in the humanities is linked to the question of what humanities scholars perceive as 'good research'. Even though scholars themselves evaluate research on a daily basis, e.g. while reading other scholars' research, not much is known about the quality concepts scholars rely on in their judgment of research. This chapter presents a project funded by the Rectors' Conference of the Swiss Universities, in which humanities scholars' conceptions of research quality were investigated and translated into an approach to research evaluation in the humanities. The approach involves the scholars of a given discipline and seeks to identify agreed-upon concepts of quality. By applying the approach to three humanities disciplines, the project reveals both the opportunities and limitations of research quality assessment in the humanities: A research assessment by means of quality criteria presents opportunities to make visible and evaluate humanities research, while a quantitative assessment by means of indicators is very limited and is not accepted by scholars. However, indicators that are linked to the humanities scholars' notions of quality can be used to support peers in the evaluation process (i.e. informed peer review).