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This paper examines the societal impact of research from the perspective of interconnected genres. Information reaches professionals outside academia through many different types of documents. Those documents often connect with scholarship by referencing academic work, mentioning professors, or publishing articles authored by scholars. Here the pattern of referencing journal articles is compared across professional genres. Such citation counts make visible societal impacts to the extent that a field engages a genre, and different genres favor different fields. Biomedical sciences are most visible in patent citation counts. News and social media most often reference medicine. Policy documents make heavy use of social science. Ulrich’s indexing of trade journals, magazines, and newspapers suggests social sciences engage heavily with the professions through trade press. However, caution is warranted when using citations to indicate societal impact. Engagement with scholarship occurs not only through referencing but also through authorship and mentions. Not all citations indicate substantive engagement, particularly in social media. Academic literature is but one of many types of sources referenced in professional genres. And scholarship engages with many genres beyond those currently indexed, most notably trade press. Nevertheless, understanding citation patterns across heterogeneous professional genres offeres a promising frontier for information sciences to provide a foundation for the analysis of scholarship’s societal impact. [ABSTRACT FROM AUTHOR]

A new indicator of technological impact of a scientific journal is presented, based on citations in patent applications to papers published in that journal. Key characteristics are that patent citations are aggregated by patent family, and that not all citations are considered equal. To each family citation a weight is assigned that is proportional to the Gross Domestic Product (GDP) of the countries in which protection is requested, to take into account the costs and expected benefits of patenting, and inversely proportional to the number of cited references in a patent family, as a way to correct for differences in citation frequencies in patent applications among technological fields. Around one third of journals indexed in Scopus have at least one citation from patent applications in a 5-year citation window. The distribution of the technological impact scores among journals can be modelled as a power law distribution, with the slope being a little smoother than that of common scientific impact indicators SJR and JIF. However, the correlations between technological and scientific impact indicators are mostly low or moderate, which shows that they measure quite different aspects of journal or research performance. [ABSTRACT FROM AUTHOR]

COVID-19 has greatly impacted science. It has become a global research front that constitutes a unique phenomenon of interest for the scientometric community. Accordingly, there has been a proliferation of descriptive studies on COVID-19 papers using altmetrics. Social media metrics serve to elucidate how research is shared and discussed, and one of the key points is to determine which factors are well-conditioned altmetric values. The main objective of this study is to analyze whether the altmetric mentions of COVID-19 medical studies are associated with the type of study and its level of evidence. Data were collected from the PubMed and Altmetric.com databases. A total of 16,672 publications by study types (e.g., case reports, clinical trials, or meta-analyses) that were published in the year 2021 and that had at least one altmetric mention were retrieved. The altmetric indicators considered were Altmetric Attention Score (AAS), news mentions, Twitter mentions, and Mendeley readers. Once the dataset of COVID-19 had been created, the first step was to carry out a descriptive study. Then, a normality hypothesis was evaluated by means of the Kolmogorov–Smirnov test, and since this was significant in all cases, the overall comparison of groups was performed using the nonparametric Kruskal–Wallis test. When this test rejected the null hypothesis, pairwise comparisons were performed with the Mann–Whitney U test, and the intensity of the possible association was measured using Cramer’s V coefficient. The results suggest that the data do not fit a normal distribution. The Mann–Whitney U test revealed coincidences in five groups of study types: The altmetric indicator with most coincidences was news mentions, and the study types with the most coincidences were the systematic reviews together with the meta-analyses, which coincided with four altmetric indicators. Likewise, between the study types and the altmetric indicators, a weak but significant association was observed through the chi-square and Cramer’s V. It can thus be concluded that the positive association between altmetrics and study types in medicine could reflect the level of the “pyramid” of scientific evidence. [ABSTRACT FROM AUTHOR]

Can alternative metrics (altmetrics) data be used to measure societal impact? We wrote this literature overview of empirical studies in order to find an answer to this question. The overview includes two parts. The first part, "societal impact measurements", explains possible methods and problems in measuring the societal impact of research, case studies for societal impact measurement, societal impact considerations at funding organizations, and the societal problems that should be solved by science. The second part of the review, "altmetrics", addresses a major question in research evaluation, which is whether altmetrics are proper indicators for measuring the societal impact of research. In the second part we explain the data sources used for altmetrics studies and the importance of field-normalized indicators for impact measurements. This review indicates that it should be relevant for impact measurements to be oriented towards pressing societal problems. Case studies in which societal impact of certain pieces of research is explained seem to provide a legitimate method for measuring societal impact. In the use of altmetrics, field-specific differences should be considered by applying field normalization (in cross-field comparisons). Altmetrics data such as social media counts might mainly reflect the public interest and discussion of scholarly works rather than their societal impact. Altmetrics (Twitter data) might be especially fruitfully employed for research evaluation purposes, if they are used in the context of network approaches. Conclusions based on altmetrics data in research evaluation should be drawn with caution. [ABSTRACT FROM AUTHOR]

The normative theory of citing considers citations as rewarding tools to acknowledge the influence of scientific works, while the social constructivist theory of citing considers citations, for example, as persuasion tools used by authors to support their claims, and convince the scientific community that those claims are valid. Other citation theories and models have been proposed in recent years to overcome the limitations of the normative and social constructivist theories. Nevertheless, they have not been able to fully explain all citation motives of scientists (but have a certain focus). This study proposes a new theory (which we call “social systems citation theory”, SSCT) that integrates previous theories and models on publications and their citation links and is mainly based on Niklas Luhmann’s “social systems theory”. Luhmann’s social systems theory focuses on “communications” as the basic constituting elements of a social science system and not on humans and their motives. Humans are not part of social systems but are connected with them and irritate them. Thus, the social systems theory does not have the problem of integrating various and different motives of humans to cite in the science system. In the SSCT, authors’ motives to cite belong to psychic systems while publications and their citation links belong to the social science system. The systems operate autonomously but interact with each other: the social system operates recursively with publications and citation links. Although psychic systems stimulate or irritate the science system, they do not determine communications in the science system. In this study, we explain the SSCT and demonstrate how the theory can be used to underlie empirical bibliometric studies. [ABSTRACT FROM AUTHOR]

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Copyright of El Profesional de la Información is the property of EPI SCP and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of El Profesional de la Información is the property of EPI SCP and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of El Profesional de la Información is the property of EPI SCP and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)