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This study analyses the thematic and conceptual structure of the Spanish scientific production published in Emerging Sources Citation Index (Web of Science) journals. In this way, the aim is to identify the closest links between concepts and terms based on the co-occurrence of keywords used by the authors of the papers analysed, and also to point out the theoretical foundations that exist in the discipline through the co-citation relationships of articles in the bibliography of the documents in the sample. Finally, these results were compared with those obtained from the analysis of Spanish scientific production in Social Sciences Citation Index (SSCI). To achieve these objectives, a network analysis of the co-occurrence of keywords and co-citation of references in articles published in Communication journals between 2015 and 2021 in ESCI (N = 3,559) and SSCI (N = 1,738) with at least one author linked to a Spanish institution was carried out. The results point to similar structural cohesion values and to a thematic and methodological similarity between both sets observed. There is a marked tendency towards quantitative studies on new technologies. While in SSCI there is an almost absolute dominance of Journalism studies, in ESCI there is a greater diversity of other disciplines such as Audiovisual Communication or Advertising. However, the intellectual structure of the production in SSCI reflects a more specialised character than in ESCI. [ABSTRACT FROM AUTHOR]

The current trends and challenges in the field of bibliometrics are reviewed. To do so, we take the reader along a bibliometric route with six stations: the explosion of databases, the inflation of metrics, its relationship to Data Science, searching for meaning, evaluative bibliometrics, and diversity and profession. This evaluation encompasses three dimensions of the bibliometrics field regarding research evaluation: the technological, the theoretical, and the social. Finally, we advocate for the principles of an evaluative bibliometrics, balancing the power of metrics with expert judgment and science policy. [ABSTRACT FROM AUTHOR]

When scientists study the phenomena they are interested in, they apply sound methods and base their work on theoretical considerations. In contrast, when the fruits of their research are being evaluated, basic scientific standards do not seem to matter. Instead, simplistic bibliometric indicators (i.e., publication and citation counts) are, paradoxically, both widely used and criticized without any methodological and theoretical framework that would serve to ground both use and critique. Recently, however Bornmann and Marewski (2019) proposed such a framework. They developed bibliometrics- based heuristics (BBHs) based on the fast-and-frugal heuristics approach (Gigerenzer; Todd; ABC Research Group, 1999) to decision making, in order to conceptually understand and empirically investigate the quantitative evaluation of research as well as to effectively train end-users of bibliometrics (e.g., science managers, scientists). Heuristics are decision strategies that use part of the available information and ignore the rest. By exploiting the statistical structure of task environments, they can aid to make accurate, fast, effortless, and cost-efficient decisions without that trade-offs are incurred. Because of their simplicity, heuristics are easy to understand and communicate, enhancing the transparency of decision processes. In this commentary, we explain several BBHs and discuss how such heuristics can be employed in practice (using the evaluation of applicants for funding programs as one example). Furthermore, we outline why heuristics can perform well, and how they and their fit to task environments can be studied. In pointing to the potential of research on BBHs and to the risks that come with an under-researched, mindless usage of bibliometrics, this commentary contributes to make research evaluation more scientific. [ABSTRACT FROM AUTHOR]

Since the end of the 1980s, citation impact values -especially for evaluative purposes- are increasingly presented as fieldnormalized citation scores than as bare citation counts or citation rates. In rather popular variants of the scores, the average score over a publication year is not exactly one due to multiple Web of Science subject categories per paper. We propose a scaling method which introduces slight changes in the field-normalized scores of each paper that ensures that the average value of all scores equals one. [ABSTRACT FROM AUTHOR]

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